WebWeaver: Structuring Web-Scale Evidence with Dynamic Outlines for Open-Ended Deep Research
Authors: Zijian Li
Xin Guan
Bo Zhang
Shen Huang
Houquan Zhou
Shaopeng Lai
Ming Yan
Yong Jiang
Pengjun Xie
Fei Huang
Jun Zhang
Jingren Zhou
Venue: ICLR 2026 Poster (2026)
Keywords: Large Language Models
Agent
Deep Research
Primary area: applications to computer vision, audio, language, and other modalities
TL;DR: A novel agent framework to achieve SOTA for open-ended deep research

Abstract: This paper tackles \textbf{open-ended deep research (OEDR)}, a complex challenge where AI agents must synthesize vast web-scale information into insightful reports. Current approaches are plagued by dual-fold limitations: static research pipelines that decouple planning from evidence acquisition and monolithic generation paradigms that include redundant, irrelevant evidence, suffering from hallucination issues and low citation accuracy. To address these challenges, we introduce \textbf{WebWeaver}, a novel dual-agent framework that emulates the human research process. The planner operates in a dynamic cycle, iteratively interleaving evidence acquisition with outline optimization to produce a comprehensive, citation-grounded outline linking to a memory bank of evidence. The writer then executes a hierarchical retrieval and writing process, composing the report section by section. By performing targeted retrieval of only the necessary evidence from the memory bank via citations for each part, it effectively mitigates long-context issues and citation hallucinations. Our framework establishes a new state-of-the-art across major OEDR benchmarks, including DeepResearch Bench, DeepConsult, and DeepResearchGym. These results validate our human-centric, iterative methodology, demonstrating that adaptive planning and focused synthesis are crucial for producing comprehensive, trusted, and well-structured reports.

Published as a conference paper at ICLR 2026
WEB WEAVER: STRUCTURING WEB-SCALE EVIDENCE WITH DYNAMIC OUTLINES FOR OPEN-ENDED DEEP RESEARCH
Zijian Li Xin Guan Bo Zhang", Shen Huang Houquan Zhou', Shaopeng Lai²,
Ming Yan?, Yong Jiang 26x0 Pengjun Xie", Fei Huang Jun Zhang's Jingren Zhou²
Hong Kong University of Science and Technology Tongy Lab, Alibaba Group
8 "Southeast University "Soochow University
zi zijian. li@connect. ust hk, Langda@allbaba-ingg ee eejzhang@ust.hu
ABSTRACT
This paper tackles open-ended deep research (OEDR), a complex challenge where Al agents must synthesize vast web-scale information into insightful re- ports. Current approaches are plagued by dual-fold limitations: static research pipelines that decouple planning from evidence acquisition and monolithic gen- eration paradigms that include redundant, irrelevant evidence, suffering from hallucination issues and low citation accuracy. To address these challenges, we introduce WebWeaver, novel dual-agent framework that emulates the human research process. The planner operates in dynamic cycle, iteratively interleaving evidence acquisition with outline optimization to produce comprehensive, citation- grounded outline linking to a memory bank of evidence. The writer then executes a hierarchical retrieval and writing process, composing the report section by section. By performing targeted retrieval of only the necessary evidence from the memory bank via citations for each part, effectively mitigates oon-cootext issues and cita- tion hallucinations. Our framework establishes new state-of-the-ar across major OEDR benchmarks, including DeepResearch Bench, DeepConsult, and Deep- iterative methodology,
ResearchGym. These results validate our demonstrating that adaptive planning and focused synthesis are crucial for produc- ing comprehensive, trusted, and well-structured reports. The code has been publicly available at ht https: : gith.b...... com/ Al wiaaabaallii. DeepResearch.
INTRODUCTION
Large Language Models (LLMs) (OpenAI, 2025b; Qwen Team, 2025; Liu et al., 2024: DeepMind, 2025; anthropic, 2025) have demonstrated remarkable capabilities across a wide array of well- defined tasks, from factual question answering (Wei al., 2025; Mialon et al., 2023) document summarization (Zhang et al., 2025) and code generation (Jiang et al., 2024). Their success, however, has largely been confined to scenarios with clear instructions and ground-truth answers. The true frontier for autonomous Al lies in transcending these structured problems to tackle the complex, open-ended challenges that define human-level knowledge work-a process driven by curiosity, synthesis, and the discovery of novel insights. We term this challenge open-ended deep research (OEDR). Unlike tasks with ground- truth answers, OEDR requires an agent to independently navigate and digest a vast corpus of information, often exceeding 100 web pages and PDFs, to form detailed report with accurate citations. This represents a monumental challenge, and as shown in Fig. 1, 2, most proprietary agents fail dramatically on report quality (RACE) and citation accuracy (FACT) of DeepResearch Bench (Du et al., 2025), highlighting a critical gap we aim to address.
Current attempts tackle OEDR fall into two main categories: proprictary and open-source solutions. While several powerful proprictary agents show strong performance (OpenAl, 2025a; Research,
Work done during an internship at Tongyi Lab, Alibaba Group.
Corresponning author.

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Published as a conference paper at ICLR 2026
DeepResearch (RACE)
DeepRese Bench (FACT)
120
*
18.00
Okadon Accueay
45.08
44.54
60
WettiNoweer (2ows5-7155=422--mm
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83
75
100
125
150
175
250
225
Figure I: Performance of varying deep research agents on DeepResearch Bench (RACE). The re- sults on DeepResearch Bench are taken from the official leaderboard. Our proposed WebWeaver achieves state-of-the-an performance and even outperforms reference answers.
Figure 2: Performance of varying deep research agents on DeepResearch Bench (FACT), Our proposed WebWeaver achieves highest effective citations and citation accuracy.
2025b;e;a), their prohibitively expensive APIs and restrictive quotas create significant barriers, limiting widespread adoption and hindering academic research. Consequently, the focus has shifted towards open-source alternatives, which predominantly follow two paradigms. As shown in Fig. 3, the first is straightforward "search-then-geene generrtt"" approach (Tao et al., 2025; Roucher et al., 2025), where the agent gathers all information before directly generating a report. This method results in low-quality, incoherent outputs because it lacks an outline to guide writing. The second, more sophisticated approach either initializes static outline to guide searching (Han et al., 2025; Research, 2025d; Researcher, 2025) or searches information for outlining (Shao et al., 2024; Xiong et al., 2025). However, these strategies are critically flawed: the upfront outline often suffers from the LLM's internal outdated knowledge. The search-first method also constrains the searching boundary without outline guidance. Furthermore, feeding all searched materials or redundant evidence into the context for final writing is susceptible to the "loss in the middle" issue (Liu et al., 2023) and increased hallucinations, compromising the report's 's accuracy and depth (Bai et al., 2024; Wu et al., 2025c).
The key, we believe, lies in abandoning rigid, machine-like pipelines and instead embracing the organic process of human intellect. Our approach designed to do just that: it teaches the agent to research like a person. A human expert doesn't 't decouple and fix their drafting and searching phases; they allow these two phases to co-evolve until converging to a comprehensive outline. We implement this principle through an agentic loop where actions of searching and outline optimization interleave. As the agent explores the web-scale information landscape, its discoveries continuously inform and reshape the outline. Critically, this refined outline then acts strategic blueprint, actively guiding subsequent searches to fill identified knowledge gaps and explore underdeveloped sections. This creates true feedback loop where outlining and discovery co-evolve. Then, when it is time write, our agent should accept only the relevant context. Just as a human writer would refer to specific notes for a specific chapter, our agent composes each section by focusing only on the source- groundd materials. By doing so, it operates with clarity and precision, crafting final report that is not just summary of data but well-structured and insightful pieces of analysis with accurate citations.
To this end, we propose Weaverver by following the human-centric philosophy, a dual-agent framework comprising a planner and writer. As shown in Fig. 3, the planner embodies the exploratory research phase, operating in dynamic, agentic cycle that iteratively interleaves evidence acquisition with outline optimization, culminating outline, where each section is explicitly linked via citations to curated memory bank of source evidence. When it turns to the writing phase, to address the critical long context and attentional context management challenge, the writer executes memory-grounder citation-driven, hierarchical synthesis process. It constructs the report section by section, performing targeted retrieval of only the relevant evidence from a structured memory bank via citations in the outline for each subtask. This synergistic division of labor enables our agent to navigate complex information landscapes and produce reports that are both comprehensive in scope and trusted in their evidentiary grounding.
comprehensive, source- garree-gounded research
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Query
Query
Outline
Report generation
Section
Report generation
Planner
Section
[OR
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Plorner
Search G
(a) Search then generate
(b) Outline Outline-guided giiiedd search search then outlining
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Report Section 1
Query
Planner
Writer
Section 2,09
Search
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(c) WebWeaver (ours)
Memoryy bonk
Figure 3: (a) the search-then-geneet paradigm first gathers information and then directly generates report: (b) the paradigms decouple the searching and outline generation; (c) WebWeaver not only enables dynamic research cycle where the outline and search strategy co-evolve but allows hierarchical and attentional writing by retrieving only relevant evidence with citations in the outline.
Extensive experiments demonstrate that Web achieves state-of-the-art (SOTA) performance and outperforms both the proprietary and open-source agent systems on three recent and challenging open-ended deep research benchmarks. Detailed discussion is produced to demonstrate the effective- ness of outline optimization and memory-grouus grounded synthesis. Critically, WebWeaver enables agentic finetuning of small models for practical use. We construct a high-quality SFT dataset, Web Weaverr-- generated by framework. The experiments with WebWeaver-3k demonstrate that the complex skills of thinking, searching, and writing can be learned, enabling smaller, accessible models to achieve the expert-level performance previously confined to large-scale proprietary systems.
PRELIMINARIES
Problem definition. We consider the open-ended research question without the ground-truth answers. Given an open-ended question, the agents need to search relevant information and finally output report or article. To achieve this, we implement planner for collecting information, a memory to store materials, and a writer for report generation. For both the planner and writer, we adopt ReAct (Yao al., 2023) as the agent's 's framework. Upon receiving question, they perform several iterations of thought-action--obsee the L.M generates thought and executes parsable action, then awaits the environment return observation. The planning and writing stages terminate with the output token of "<terminate>". A complete trajectory with T' iterations can be defined
Specifically, in each iteration, based on the existing context,
Hy (Tos ag Og.... Ti ag O,. Tr, ar),
(I)
where Tú, as O; represent thought, action, and observation sampled from the planning or writing policy based on all previous context in the i-th round, respectively.
Actions. For the planner, the action space consists of search, write outline, and terminate. Given the search queries, the search engine returns titles, snippets, and corresponding URLs. To save context space, we further execute the actions of URL selection, parsing pages via URLs, summarizing relevant contents, and extracting evidence with LLMs following the searching queries. The search tool finally returns the selected URLs with their corresponding summaries and evidence. The action of "write outline" is to generate and optimize the outline with citations linking the evidence in the memory bank, and the "terminate" action to terminate the planning process.
For the writer, the action space consists of retrieve, write, and terminate. Besides the terminate action, the retrieve action is to retrieve evidence from the memory bank by providing the grounded citations in the outline. The write action is provided write the section of the report.
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Published as a conference paper at ICLR 2026
Query
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Appliostion Sports Intellgent
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Figure 4: The workflow of WebWeaver. Left: The planner first iteratively collects evidence via the search action and optimizes the outline until outputting comprehensive and -rradinn-roouned outline. Right: The writer performs hierarchical and attentional writing by retrieving relevant evidence with the grounded citations the outline.
Memory bank. Answering an open-ended question requires long-context input of the collected information and long-contexs output of the final report. To search sufficient materials, the planner often searches and parses more than 100 web pages, with more than 100k tokens. The writer often outputs more than 20k tokens produce comprehensive report. Prior open-sourced deep research agents (Roucher et al., 2025; Research, 2025d; Researcher, 2025) include all the raw materials (e.g., web pages and PDF files) in the LLM context, leading to quality degradation due to attentional failures like the "lost in the middle" problem, poor coherence, and increased hallucinations (Liu et al., 2023; Li et al., 2024a; Bai et al., 2024; Wu et al., 2025c). To this end, introduce memory to achieve context management for both planner and writer. Only a short summary of the web page or PDF file is included in the search context, and only necessary raw pages will be retrieved from the memory to write the corresponding sections via the citations in the outline.
METHOD
Our methodology embodied a dual-agent framework, comprising a planner and a writer. The planner is responsible for the dynamic cycle of evidence acquisition and outline optimization, while the writer performs evidence-grounder section-by-section synthesis to construct the final report. This division of labor directly mirrors the cognitive workflow of human researcher. The entire workflow is visualized in Fig. 4.
The planner operates dynamic, agentic research cycle. It iteratively interleaves evidence ac- quisition from web searches with the continuous refinement and optimization of report outline. The output of this exploratory phase is not just collection sources but a comprehensive. well- structured outline where each section is explicitly linked via citations to a curated memory bank of source evidence. Subsequently, the writer takes over for the synthesis phase. To circumvent the pitfalls of brute-force generation and noisy-context issues, the writer adopts a section-wis and memory- grrondddd synthesis approach. For each section the outline, it performs targeted retrieval of only the pertinent evidence from the memory bank using cations and composes the content. This division of labor ensures that the final report is not only coherent and well-organized but also deeply source-grood grounee, faithfully mirroring the rigor of human-led deep research.
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Published as a conference paper at ICLR 2026
3.1 RESEARCH CYCLE: ITERATIVE EVIDENCE ACQUISITION AND OUTLINE OPTIMIZATION
Recent deep research agents primarily follow two distinct, yet equally flawed, paradigms that decouple planning from discovery. The first, an "outline-guided search" approach (Han et al., 2025; Research, 2025d; Researcher, 2025), generates a static outline before any evidence is gathered. This rigidly confines the research to the LLM's internal, often outdated knowledge, making it blind to emergent approach (Shao et al., 2024; Xiong et al., 2025),
insights. The second, a "search-then-outining performs an initial, broad search and then generates fixed outline based these preliminary findings. This approach permanently constrains the research scope to what was discovered in the initial, undirected search. Despite their different ordering, both paradigms share the same critical limitation: their one-way workflow prevents adaptation. In contrast, we propose a dynamic research cycle where the outline and search strategy co-evolve, creating feedback loop that allows the planner to continuously adapt and explore in response to new findings.
The core of our planner's operation is dynamic research cycle that iteratively interleaves evidence acquisition with outline optimization. Unlike static approaches, our planner continuously adapts its strategy based on emergent findings. For each step, the planner selects one of the three actions: search, write outline, and terminate.
Evidence acquisition. When the planner thinks that there is still insufficient evidence or knowledge to make a comprehensive outline to answer the open-ended question, it will continue collecting evidence by executing the search action. Given any search queries, the planner begins by querying a web search engine, which returns the results that contain the raw URLs with corresponding snippets and titles. To combat the contextual noise and processing overhead from raw URLs, it employs a two-stage filtering process. First, we prompt LLMs to select only the relevant URLs based on titles and snippets. Then, for each parsed page of the selected URLs, we perform two critical actions: leveraging LLMs to (1) distill query-relevant summary, which is fed back into the planner's context to inform subsequent search iterations, and (2) extract verifiable, detailed evidence (e.g., quotes, data points), which is stored in structured memory bank for the subsequent writing.
Outline optimization. After acquiring some evidence, the planner revisits the report's 's outline. This is not a one-time generation step but process of continuous refinement and optimization. The planner uses the newly acquired information to expand sections, add citations, or even restructure the entire outline to better reflect comprehensive understanding of the topic. Crucially, populates the outline with citations, mapping each section to the specific evidence IDs in the memory bank. This citation mechanism vital for ensuring source-grone groree-goundedeess and supporting the subsequent hierarchical writing stage. This iterative loop continues until the planner outputs terminate action with tag "<terminate>" when the outline is sufficiently comprehensive and well-supported by evidence.
3.2 MEMORY- GROUNDED SYNTHESIS: HIERARCHICAL RETRIEVAL AND WRITING
A pivotal challenge in generating long- reports is not just information access but attentional management. The prevailing approaches of feeding all gathered evidence (Bai et al., 2025; Xiong et al., 2025) or redundant content from retrieval (Shao et al., 2024) saturate the model's 's attentional capacity, leading to the increased hallucinations (Liu et al., 2023), where crucial details are overlooked, and "contextual bleeding" (Liu et al., 2025), where information from one section incorrectly influences the synthesis of another. We argue that a successful synthesis process must mirror human cognition by breaking down the complex task of long-context writing into manageable subtasks of attentional writing with only correct, relevant evidence. Therefore, we adopt hierarchical, citation- grounded strategy, where the report is constructed sequentially, with the grounded retrieval of evidence using citations in the outline to enhance the writing correctness.
Upon completion of the planning phase, the writer is provided with the structured, source-grounded outline and access to the evidence memory bank. The composition of each section is not single, monolithic action but a deliberate, intra-sectional reasoning cycle designed to ensure both accuracy and coherence. This cycle unfolds follows:
First, the writer identifies its immediate subtask, such as "Let's write the first section." " It then executes targeted retrieval action, pulling only the relevant evidence from the memory bank as indicated by the outline's 's citations. With evidence, the writer enters a crucial reasoning phase with a think action. It analyzes the previous sections and retrieved content, synthesizes key insights, selects the
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RACE
FACT
Agent systems
Overall
Comp.
Insight
Inst.
Read.
Rft.
C. nec.
OpenScholar
25,56
21.38
15.49
38.58
29.77
WebShaper
ReAct (Qwen3-255)) 2563 a22b instract-2507)
46.16
45.04
43.2
49.16
46.17
Smnccain--gee-de---cee
43.44
42.97
39.17
48.09
45.22
douboo-research
44.34
44.84
40.56
47.95
44.69
52.62
52.86
kimi-research
41.97
45.59
Clauderescarch
45.00
45.34
42.79
47.58
44.66
openai deepresearch
46.45
46.46
43,73
49.39
47.22
39.79
75.01
Gemini-2.5 2-miiii-5-pro-dopppeee pro-doppreeeeucch
49.71
49.51
49.45
50.12
50,00
165.34
78.30
WebWeaver (incaa--00--30---ttooo-----0
45.78 (0.7)
44.44 (0.5)
45.10 (0:5)
48.16 (0.8)
45.32 (1.2)
22.34 (2.6)
25.29 (0.9)
WebWeaver (GPT-oss- 120h)
47:71 (0.8)
47.38
46 46.86 (0.1)
48 (0:5)
48.85 (0:5)
66,83 (1.5)
67.03 (0.5)
WebWeaver (i0aa--255-a22b-nnstte
(0.1)
(0.1)
(0.2)
WebWeaver (Claude 2ommee---20220000
50.48 (0.1) 31.65 (0.1)
49.67 (0.31
$0.57 (0.1)
49.72 (0.1)
216.99 (6.3) 92.13 (0.7)
Table I: Performance of agents on DeepResearch Bench in terms comprehensiveness (Comp.), insight, instruction-followingg (Inst.), readability (Read.), effective citations (Eff. c.), and citation accuracy (C. acc.). The best results are highlighted with purple color, and the second-hes, results are highlighted with underlines. Standard deviations are present in bracket.
most compelling pieces of evidence, and formulates coherent narrative structure for the section. This internal monologue is critical for moving beyond simple summarization genuine synthesis.
Only after this internal analysis is formed does the writer proceed to the writing action, composing the prose and encapsulating it within "<write>" tags. Once a section complete, corresponding souree materials are explicitly pruned from the context window and replaced with placeholder message. This dynamic retrieval-and and--runing mechanism is the cornerstone of our approach: ensures the writer's s context remains highly relevant and coherent for the next cycle, mitigates context overflow, and prevents cross- coos-seectionl interference. This entire process repeats hierarchically for all sections until the writer outputs "<terminate>" token, signaling the completion of the full report.
EXPERIMENTS
In this section, first evaluate WebWeaver on three recent and challenging benchmarks. Detailed discussion is then produced to demonstrate the effectiveness of outline optimization and memory- grounded synthesis. Furthermore, the capabilities of thinking, searching, and writing for a smaller model to achieve expert-level performance, which is provided in Appendix C.
curate high-quality SFT dataset, WebWeaver-3k, to improve
4.1 EXPERIMENTAL SETUPS
Benchmarks. To evaluate the performance of Deep Research systems, we use three open-ended benchmark datasets: (1) DeepResearch Bench (Du et al., 2025) comprises 100 PhID-level complex research tasks meticulously formulated by domain experts across 22 distinct fields, such as Science Technology, Finance Business, Software Engineering, and Art & Design. (2) DeepConsult (Consult, 2025) is specialized collection of prompts tailored for in-depth research within the business and consulting domains. The query set encompasses a wide range of topics, including marketing strategy, financial analysis, emerging technology trends, and business planning. (3) DeepResearchGym (Coelho et al., 2025) is used assess performance on real-world, complex queries. This dataset contains 100 queries sampled from the extensive Researchy Questions dataset (Rosset et al., 2024), which includes approximately 96,000 authentic information-seekinn queries. The metrics of the benchmarks are detailed in Appendix B.
Compared systems. We benchmark the performance of Web Weaver against a range of state-of-the- art DeepResearch systems. These systems are categorized into two groups: (1) Open-Source Systems: For open- open-source counterparts, we compare against OpenScholar (Asai et al., 2024), WebShaper-22 (Tao al., 2025), and the widely-used ReAct paradigm (Yao et al., 2023) equipped with the identical backbone LLM -inen-22bbaa30--issttaee
(LangChain, Inc., 2023). We also include
and the same tools; (2) The Powerest Proprietary Systems from

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DeepCrnsatt
Despleeeacchmm
Agus syseee
Vin
Avg. sour
Clk
Degeh
Bak.
Bres
5up.
Ens.
Ang.
WetSaann (328)
66.50
$3,50
29.85
40.35
5.42
88.55
98.33
15:30
38
36.11
4.00
56.57
95.38
6441
96.35
26.77
90.22
50.25
0.00
100.00
0.00
5,00
$6.00
98.10
89.80
97.40
89.40
19.00
91.27
Genini geo Japposaa
61.27
31.13
6.70
96.71
99900
03.32
97.45
96.92
0..1
WebWeaser (Qwee3 215h indtrattdddt-- 2207))
(07,8
06
1..3
14:37
1900
89331
10.3)
99 15 (0.11
91.95
00:01
99.25 (11)
06.7011.23
95.45 0L3)
95.57 (L4)
WelWesser (Clasce sosect- 31250614)
(1.9)
12:1413
21,85 98.7
1833
50.37 19.31
09.96 (83)
94.13 00.31
09.30.00)
98.99
(02)
96.74
Table 2: Performance of agents on DeepConsult in terms of win rate and average scores and on DeepResearchGyym in terms of clarity (Cla.), depth, balance (Bal.), breadth (Brea.), support (Sup.), and insightfulness (Ins.). The best results are highlighted with purple color, and the second-best results are highlighted with underlines. Standard deviations are present in bracket.
DeepResearch Bench leaderboard (up to Sept. 25, 2025): doubao-research (Research, 2025a), kimi-research (Research, 2025c), Claude-research (anthropic, 2025), ppena--deepresearch (OpenAI, 2025a), and
(Research, 2025b).
Implementation details. The WebWeaver is compatible with various advanced LLMs. In the experiments, we utilize the following models: Qwen3-30nk -aaa--330002bb--nstuttt---- GPT-oss- 120s (Agarwal et al., 2025), wwen3-235bba22b-isstuet moude-sonnet-4-22555
(Yang et al., 2025), (Yang et al., 2025), and 14 the default agent model for ablation studies and discussion without any statements. We use GPT-oss- --T--os--20bb to select relevant URLs, perform query-relevans summaries, and extract evidence for the search action. We run three independent runs and report means and standard deviations. The detailed cost analysis is discussed in Appendix F. We present the prompts and case studies in Appendix I.
14 (anthropic, 2025). We adopt Claude-somnet-422022
4.2 MAIN RESULTS
Results on DeepResearch Bench. As presented in Table 1, our WebWeaver framework establishes new state-of-the-art consistently outperforming existing agents. This superior performance is a direct result of our dual-agent, iterative methodology. The high scores in comprehensiveness (Comp.) and insight stem from the planner's 's dynamic research cycle, which iteratively expands the report's 's scope based on emergent findings. This process naturally leads to a higher number of effective citations (Eff. c.), as the planner is intrinsically motivated to seek more evidence to ensure that each section is well-supported. Furthermore, the remarkable citation accuracy (C. acc.) of 92. 13% is achieved by the strong synergy between our agents: the planner embeds specific citation IDs into the outline, and the writer's hierarchical synthesis process uses this structure for targeted retrieval. By focusing only on relevant evidence for each section, it drastically reduces context-bleeding and hallucinations, which also contributes to the enhanced readability (Read.), accuracy (C. acc.). This demonstrates that by emulating human research patterns, our framework produces not just more thorough but also significantly more reliable and well-structured reports.
(Inst.) scores, and citation
Results on DeepConsult and DeepResearchCym. To validate its generalizability, we evaluated WebWeaver on DeepConsult and DeepRescarchhym (Table 2), where it achieved the highest win rate (67.69%) and top average score (96.74), respectively. This success is rooted in our core design: the planner's iterative cycle ensures near-perfect depth and breadth, while the writer's 's hicrarchical synthesis guarantees outstanding balance and support. These quantitative strengths in structural metrics directly explain the qualitative victories, proving the robustness of our writing strategy. A detailed human evaluation is present in Appendix further demonstrate WebWeaver's superiority in report generation.
4.3 ANALYSIS
Statistics of planning and writing. The statistics in Table 3 provide a compelling quantita- tive narrative that not only justifies but also demonstrates the benefits of WebWeaver's design.
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Planning statisties
Writing statistics
Search
Outline
Outline
Saved
Scarch
# Evidence
Summary
Outpat
Writing
step
token
aptimization
page
query
token
token
token
step
DeepRevearch Bench
2.16
DeepResearhCyy
16,83
373287
2.20
102.5
21.93
66:01
12543
26004
24.71
Table 3: The planning and writing statistics of Claude-sommet-42202335114 on benchmarks.
The planning task involves an extensive ex- ploratory phase with nearly 16 search steps and 21 unique search queries, proving that a sim- ple, linear search is insufficient. The critical finding is that the outline undergoes more than two optimization cycles on average, expanding into a complex 4k-token outline. This empiri- cally invalidates static-outline approaches and shows the tangible benefit of our iterative pro- cess: produces richer, more comprehensive plan that adapts to discovery. This deep plan- ning phase amasses a staggering amount of in- oormation-over 100 saved pages, culminating in 67k evidence tokens and 15k summary tokens. This sheer volume makes brute-force approach
De-pResearch Bench
DeepResearchéym
round
rounds
1 round
rounds
15.0%
13.19
rounds
25.3%
59.0%
57.6%
2 rounds
2 rounds
Figure 5: Statistics of outline optimization of Claud--someet442222561 on DeepResearch Bench and DeepResearchGym.
computationally hard, thus mandating our memory-centric architecture with targeted retrieval as foundational requirement, not just an optimization. Finally, the writer's process of composing 26k-token report in 25 discrete writing steps validates that our hierarchical synthesis is a practical way maintain coherence over long outputs. In essence, the statisties of searching and writing affirm that each component of Web Weaver is a necessary and beneficial response to the inherent challenges of OEDR.
Superiority of outline optimization. To isolate and quantify the benefits of outline optimization, as reported in Fig. 6, 7, we conducted an ablation study by evaluating the end-to-end benchmark performance. We collect the samples with three-round outline optimization from DeepResearch Bench and DeepResearchGym, adopting the same writing strategy for them. The first-round optimized outline scenario does not guide searching here, which is similar to the planning paradigm of the prior work STORM (Shao et al., 2024).
Rounds
Rounds
Round
195
Round
Round
Round
AAM
2G-
32-
30
Unvred Searen Soggrebassteeees Beight Betrasiien Intwwing Pooabiiiity
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33
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Evaluation
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Figure 6: End-to-end scores with varying rounds of outline optimization DeepResearch Bench.
Figure 7: End-to-end scores with varying rounds of outline optimization DeepResearchGymm
The benefits of this iterative refinement are evident across both benchmarks. On DeepResearch Bench, the overall score steadily climbs, driven primarily by significant gains in comprehensiveness (48.85 - 50.82) and insight (46.33 - 48.35). This directly validates our hypothesis that each optimization round allows the planner to build a more detailed and logically structured outline. This enhanced structure is further reflected in DeepResearchhym' 's metrics, where later rounds achieve near- perfect scores in depth (100) and breadth (99.58), indicating a more exhaustive topic coverage. Crucially, this is not just about adding more content; the steady rise in support (95.91 98.33) demonstrates
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that more refined outline creates better-scaffolded structure, enabling the writer more tightly link claims to evidence. In summary, this analysis empirically demonstrates that iterative outline optimization is not redundant step but critical mechanism for elevating report from a simple summary to a deep, insightful, and well-supported piece of research. We also provide L.M as a judge (Zheng al., 2023) for multiple-round optimized outlines in Appendix G.
Duepfeeaeerh Bench
DeepResearchdym
Whitig 324 Hinesta 60
Longlh Eiauctioa Wall
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Figure 8: Performance comparison between hi- erarchical writing and brute-force writing (Long- Writer) on DeepResearch Bench.
Figure 9: Performance comparison between hi- erarchical writing and brute-force writing (Long- Writer) on DeepResearchGym.
Hierarchical retrieval and writing vs. brute-force writing. To empirically validate our hierarchical writing process, we conducted a critical ablation study comparing our hicrarchical writer against brute-force baseline that attempts to include the entire memory bank to generate the final report in multiple steps, which is similar to the workflow of LongWriter chunking here without exceeding the context limits of Writer (Bai et al., 2025). No evidence 14. The results in Fig. 8, 9 are unequivocal: our hierarchical approach dramatically outperforms the brute-force method across every metric, confirming that hierarchical writing strategy is essential. The most striking improvements are in insight (42.72 - 49.47) and readability (43.82 - 49.72), which directly val- idates our hypothesis on attentional management; by focusing the model on a curated context for each section, it can perform deeper reasoning rather than shallow summarization. Furthermore, the accurate retrieved content using citations also brings higher citation accuracy (86.73 + 92.13) and supportiveness (90.95 - 98.69). In conclusion, these results provide definitive evidence that emu- lating the human cognitive process of focused, Dection-by-seetinn writing is not merely a beneficial choice but fundamental requirement for generating coherent, insightful, and reliable long-form reports.
Context management superiority. The con- text management superiority of our hicrarchical writing process is quantitatively validated in Fig- ure 10. At each individual writing step, our method provides the model with significantly smaller, more focused context compared to the brute-force baseline. This design dramatically reduces the model's 's cognitive load. Freed from the burden of navigating cluttered and noisy context, the writer can perform more thorough synthesis for each section. This leads to richer output that cumulatively grows with each step, and as the plot clearly indicates, surpasses the baseline in total output tokens precisely at step 6, ultimately generating a substantially longer and more detailed final report. This demonstrates that the key to producing extensive and well-developed content lies not in overwhelming the model with information, but in providing the right information at the right time.
Harracchccl Writing Brote-Force Writing
Than briteeforce wrlling stap
has input tooen conspared with trute-forca writin.
writing
Step Numbber
Output taken Runberof Writing
bokan Humber Illearciiaal Witting)
Figure 10: Input and output token statisties of souude-sonnet-4222225 14 for hierarchical and brute-force writing on DeepResearch Bench.
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5 RELATED WORKS
Open-Ended Deep Research. Deep Research Agents have garnered significant attention for their powerful capabilities in information seeking, integration, and reasoning. Proprietary systems, such as DeepResearch (OpenAI, 2025a), Gemini Deep Research (google, 2025), and Claude Research (anthropic, 2025), have demonstrated performance comparable to human experts in domains like fact-checking and report writing. However, their opaque internal architectures and workflows hinder broader research and development. the open-source community, many studies (Li et al., 2025b; Tao et al., 2025; Su et al., 2025; Qiao et al., 2025; Fang et al., 2025; Li et al., 2025a; Wu et al., 2025b;a; Li et al., 2024b; 2025c; Guan et al., 2026) have been developed to tackle complex research (QA) benchmarks. Nevertheless, these solutions are primarily tailored for short-answer research queries and lack the capability to generate comprehensive. long-form reports on open-domain topics. Other open-source systems like OpenDeepResearch (Research, 2025d). GPT Researcher (Researcher, 2025), and TTD-DR (Han et al., 2025) address long-form generation by first drafting a statie framework, then retrieving content, and finally composing the report. This approach, characterized by a fixed structure and one-step generation, often leads to textual incoherence and hallucinations. While recent works like STORM (Shao et al., 2024) and SCISAGE (Shi al., 2025) utilize searched content to generate or refine the outline, the search-first method also constrains the searching boundary without outline guidance. In addition, WriteHere (Xiong et al., 2025) also proposed to divide the writing task into multiple subtasks and search the subtasks locally. In sharp contrast, Web Weaver enables truly synergistic research cycle where the outline and search strategy co-evolve, allowing emergent findings to continuously reshape the research direction in global view.
Question-Answee
Long Writing. Ensuring the coherence and accuracy of LLM-generated long-form text a persistent challenge. Previous work has explored methods like recursive prompting for story extension (Yang ct al., 2022) and structured task decomposition to improve consistency (Yang et al., 2023; Wang et al., 2025; Huot et al., 2025). More recently, agent- base frameworks have become mainstream solution. Systems like LongWrite (Bai et al., 2025), and CogWriter (Wan et al., 2025) employ a "plan-then-write" strategy, where planner first creates an outline, and writer then conditions this plan to produce the full text. However, these methods rely on a static initial plan and a brute-force writing strategy by feeding all the evidence into LLMs. In contrast, our approach uniquely enables the outline to be dynamically optimized in tandem with the evidence acquisition process, allowing for a comprehensive, source souree-gounded research outline. While recent works (Huot al., 2025; Shao et al., 2024) adopted the multi-agen paradigm to write sections in parallel, with evidence retrieval based on the section title, the separate writing often leads to content and style incoherence, and the retrieval using titles also brings noisy evidence. In contrast, our agentic hierarchical writing model is designed to foster both global coherence and local depth. Its sequential, single-agent process allows cross-sectional thinking by maintaining continuous narrative flow between sections. At the same time, its reliance on precise, citation- grounded evidence enables deep internal reasoning within each section. This combination allows the writer to produce cohesive, accurate, and insightful report.
citation-grounded
6 CONCLUSION
In this paper, introduced WebWeaver, novel dual-agent framework designed to overcome the fundamental flaws of static, machine-like pipelines in open-ended deep research (OEDR). By emulating the human cognitive process that integrates the planner's dynamic research cycle with the writer's hierarchical retrieval and writing process, WebWeaver consistently outperforms both proprictary and open-source systems, establishing a new state-of-the-art.
Beyond its superior performance, the true significance of WebWeaver lies in the paradigm for tackling informatiioniineenivy tasks. It demonstrates that intractable long-context input and output can be deconstructed into a solvable problem of system-level context management, orchestrated through deliberate, tool-driven actions. This work, therefore, does not just present better agents but offers a new system blueprint to master knowledge through purposeful action, not brute-forc attention. Looking forward, the development of agents capable of autonomous, adaptive context management represents the next frontier in achieving truly effective and efficient artificial intelligence.
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ETHICS STATEMENT
This work adheres to the ICLR Code of Ethics. The WebWeaver agent is designed to be responsible web citizen. It programmatically respects robots.txt directives, and all web access is conducted for non-commercial academic research, aligning with fair use principles often permitted under website terms of service. Furthermore, we have implemented safeguards regarding Personally Identifiable Information (PII) at multiple stages. Our dataset curation process includes mandatory step to anonymize personal informaton. During live evidence extraction, the agent's prompts are designed to focus on factual evidence about the queries. Beyond these specific measures, we have taken steps to identify and mitigate potential biases in data selection, model prompting, and system design to ensure fairness and avoid harmful outcomes. The system is developed solely for research purposes, with these safeguards in place to minimize misuse. No human subjects or animal experiments were involved in this study.
REPRODUCIBILITY STATEMENT
To ensure the reproducibility of our work, we provide detailed information regarding the training details, prompts, and case studies. Appendix C this paper includes the training details for our agentic finetuning. The prompts and case studies of planner and writer are detailed in Appendix
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Appendix
A USE OF LARGE LANGUAGE MODELS
In adherence to ICLR 2026 policy, we disclose the assistive use of Large Language Models (LLMs) in the preparation of this paper. The models were employed to refine grammar and improve the clarity of the text. Furthermore, LLMs function as the agents for the open-ended deep research. The authors have reviewed all LLM-generated contributions and take full responsibility for the content and integrity of this work.
B EXPERIMENT DETAILS
Search tool. Weaver accesses the Google search engine for information retrieval. It allows searching multiple queries simultaneously and returns the top- 10 results for each query. Each result contains a title, a snippet, and the corresponding URL. To parse the web pages and pdf files, ScraperAP[ is first used to retrieve their full content, and then summary model extracts relevant information based on the goal. In this paper, we use GPT-oss- 120b as the summary model.
Metrics. We use the official evaluation metrics with the recommended judge LLMs of each benchmark. (1) DeepResearch Bench. This benchmark utilizes suites of metrics evaluate different aspects of the system's output: 1) RACE (Report Quality): It assesses the quality of the final generated report with reference report across four dimensions, namely Comprehensiveness (Comp.), Insight/Depth (Insight), Instruction cestuction-Followingg (Inst.), and Readability (Read.). An overall score is then calculated as weighted summation of these components. 2) FACT (Web Retrieval); measures the effectiveness and reliability of the information retrieval process. This includes Citation Accuracy (C. Acc.) and the Average Effective Citations per Task (Eff. c.). We adopt Gemini-2.5. as the judgement model by following the benchmark. (2) DeepConsult. Performance on this
benchmark is determined through a pairwise comparison against the openai-deepsearch baseline. The primary metrics are the win rate, tie rate, and loss rate, which supplemented by a reported average quality score. The judgement model is gpt-4. 1-204..-2020144 (3) DeepResearchGym. An LLM acts judge to assess the generated report several quality dimensions, including clarity, insightfulness, depth, balance, breadth, support, and an average quality score. The judgement model gpt-4.1 1-mini-20250414
Planning statistics
Writing statistics
Search step 14.67
Outline token 4148.57
# Outline optimization
Saved puge 106.65
Search query 18.8
# Evidence token 62637
# Summary
Output token
Writing
token 14155
step
WebWeaver-B3 3k
2.18
22637
22.76
Table The planning and writing statisties of training data on WebWeaver-3k.
C AGENTIC FINETUNING
While 30B-scale LLMs (e.g., 1as-m---0b--bb-nnsttut------
possess strong foundational capabilities, they often exhibit deficiencies in stability and instruction-followe when executing complex, multi- turn tool-calling sequences over long contexts. To bridge this critical gap, we constructed a high- quality Supervised Fine-Tuning (SFT) dataset: Weaverrr.. The process began by sourcing diverse set of queries crawled from the web.
We crawled web pages from curated list of high-quality English and Chinese forums and communi- ties, specifically targeting know mowleegg-intensive sources like Reddit. Our query generation process involved two main stages: We first used pattern matching to extract large pool of potential queries. This included text from specific HTML tags (e.g., <h1>, <h2> post titles) and sentences ending with question mark, resulting an initial of over candidates. We then utilized LLM to filter and
Phtpps: https:///wwwweeo htwp:////wwwsccrprpppp...oo
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Agentic Finetuning
160
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60.09
Weaver
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Benchmark
Figure 11:
Round statistics of outline optimization on WebWeaver-3k.
Figure 12:
Performance improvement of agentic fine- tuning benchmarks.
refine these candidates into high-quality, open-ended questions. Each candidate was evaluated using carefully designed prompt that instructed the model to assess it against several criteria:
Open-endedness: Does the question require detailed, synthesized report?
Clarity: Is the question well-posed and unambiguous?
Feasibility: Can evidence be found on the public web?
Refinement and Anonymization: If question has potential, refine it to the above standards and remove any personally identifiable information.
This yields queries that are more general compared to expert benchmarks that contains rich domain knowledge. To illustrate the fundamental stylistic difference:
An example from DeepResearch Bench:
"Research Topic: Crafting Techniques for Non- A Acoholic Cocktails. Objective: Investigate current non-alcoholic cocktails to discover innovative production methods and formulations."
A representatiie example from WebWeaver-3k. "What do you think about DeepSeck?"
Second, our dataset WebWeaver-34 is topically diverse and semantically different with benmarks. Its domain distribution is shown in Table which covers ten domains. The Average maximum N-gram simiarlities between WebWeaver-P5 and benchmarks are shown in Table 6. WebWeaver-33 achieves significantly low average maximum similarity (0.017 with DeepResearchGymm when N=3), demonstrating that WebWeaver-3k does not induce any text exposure.
These refined queries are then processed by a powerful, tier teacher model (Claude-sonnet-4 20250514), 1)) instantiated within WebWeaver agent framework. A stringent filtering protocol was applied to the resulting end-to-end research trajectories, retaining only those where the agent successfully executed the entire workflow and strictly adhered the predefined action format. This quality control yielded a curated dataset of 3.3k high-fidelity planning trajectories and 3. k. writing trajectories. As detailed in Table 4 and Fig. 11. these trajectories encapsulate the profound complexity of the OEDR task, with an average case involving approximately 15 search steps, over two outline optimizations, and the processing of over 62,000 evidence tokens. We performed full- -alamerteettr supervised fine-tuning 1000 iterations on NVIDIA H20 GPUs using a learning rate x 10-6, By fine-tuning our base model on this data, explicitly imbued it with the requisite long- long-sequence reasoning and tool-use capabilitics to master our framework.
with WebWeaver-Fe The model was trained for
The efficacy of our SFT strategy is quantitatively demonstrated by the significant performance gains across all benchmarks on Fig. 12, which directly reflect the model's 's acquisition of our framework's competencies. The most dramatic validation is the leap in citation accuracy from nearly unusable 25.29% to a reliable 85.90%. This provides direct, empirical evidence that the model has mastered the intricate mechanies of our Writer agent, learning to execute precise tool calls for
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Technology &Science
Academics &Education
Entertalnment
Economics
Sports
Work &Life
Politics
Culture
Society
History
&uuinnss
Ratio
23,9
16.6
16.4
15.4
7.8
5.9
4.7
3.4
3.2
2.3
Table 5: Domain distribution of WeaWeaver-3k,
Deep Bench
DeepConsult
DeepResearchGym
2-Gram
0.096
0.078
0.054
3-Gram
0.033
0.027
0.017
Table 6: Average maximum N-gram similarity (N=2, between WebWeaver-3k and benchmarks.
evidence retrieval and faithfully write according to the source- serree-grouned outline. Furthermore, the substantial increase overall report quality, evidenced by the score on DeepConsult (3.99 - 6.09) and the massive jump DeepResearchGym (77.61 + 90.89), reflects the successful acquisition of the planner's more abstract abilities. These holistic improvements indicate that the model has learned the core loop of thinking (iteratively optimizing the outline) and searching (adaptively acquiring evidence), which is a prerequisite for generating a comprehensive and insightful final report. Ultimately, these results offer powerful dual validation: they prove that WebWeaver framework is a potent data generation engine, capable of deconstructing the formidable OEDR task into learnable demonstrations of thinking, searching. and writing, thereby enabling smaller model to achieve expert-level performance.
D ABLATION STUDIES OF SUMMARY MODELS
For complex long-input, long-output tasks like open-ended deep research (OEDR), which requires collecting information from numerous web pages, intermediate steps like URL selection and evidence extraction are not just optimizations but necessary engineering practices to manage the context length. To test whether our framework's ' success is critically dependent on the model used for this necessary step, we conducted an ablation study. We replaced the powerful GPT-oss- -os--os--20b model Sowen-30b-a33 bab-aab-instruet-5500) for these tasks. The results in Table show little performance drop (from 96.74 to 96.68 DeepResearchGym) for that our framework is robust and not overly sensitive to the specific model used for these sub-tasks. This confirms that the overwhelming majority of the performance gain is attributable to core architectural innovations.
120b model with smaller
demonstrating
E HUMAN EVALUATION
To complement our LLM-as-judge evaluations, we conduct a targeted human study for qualitative validation. We invite three PhD students with research experience for blind, side-by-side comparison of our WebWeaver CCludde-onnet-4)) against the subset of 15 samples from three used benchmarks. Evaluators 'Loss', or 'Tie' across six key dimensions: Instruction Following, Depth, Balance, Breadth, Support, and Readability. The criteria for human evaluations shown below.
p...------p---eeeeerreee baseline on a random
asked determine 'Win',
The results, summarized in Table 8, show a strong and consistent human preference for WebWeaver across all evaluated dimensions. Our system demonstrated particularly dominant performance in key areas, achieving 76% win rate in Support (Failfulness) and over 69% win rate in Depth. This study provides strong validation that aligns with our larger-scale LLM evaluations.
DeepResearch Bench
DeepConsut
DeepRescarchGym
GPT-oss- 120b 0wens-330-aabb-issttt---7777
50.48
6.94
96.74
50.39
6.97
96.68
Table 7: Ablation studies with varying summary models.
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Following
Depth
Balunce
Brendth
Support
Readubility
Win
Loss
Tie
Win
Loss
Tie
Win
Loss
Tie
Win
Loss
Tie
Win
Loss
Tie
Win
Loss
Tie
WebWesver
(Clude--snnet-))
Table Human evaluation of Web WebWeaver (Claude-sonnet-4) and G on random subsets (15 samples) of three benchmarks.
Human Evaluation Criteria
Instruction Following
"* "Dexriptionn" Evaluate how well the report follows the user's instuctions. This includes topic and scope, andience, purpose, constraints, requined sections, level of detail,
formatting length requireents. Check if includes required structural elements executive summary, background, methodology, analysis, mcoomesssiions references, appendizes),
fomanting coreet. requirements are met. Penalize missing requined elements, inclusion prohibited ttems, incerrect seupe level, or devintion from requested furnal.
lugically, length
2. Depch
-a -Descripion:" Assess the comprehemsioenes and analticall depth the report's content. Hlihh-deth reports beyand surface-leve deseriptions geovide detailed analysas, explain underlying mechanisms cansal daivers, and fully substantiate key arguments. They explore behind a phenomenon, not just the "wbat." The unalysis thorough. accounting for numnc,, complexity, and underlying assumptions. Shalkow reports comsist of broad, unsubstamiated chaims, simple recitasion of facts withoul analysis vonclusions presenied without the supperting reasening.
"why"
Balance
report. Strong reports present multiple perspectives coutteraguuents fairty giving upprupriate weight to competing views and evidence, and use neutral, non- non-leatiog leading langunge throughoot. Where besues are contrveersill mulii facesed. the report explicttly discusses trae offs, limitzionn of the analysis, and sigaificatt counter evidence. Poor reports display bias, us emotive language, give salient upposing views.
"Description:" Evaluate fairness and objectivity
digroppctionatc space
side without justification.
"Desctipion""" Evaluate how many distinct and relevant subtogics, persectivee, or contets the repoct covens while staying focused on the bcief. Excellent reports integrate appropriate dimensions such histerical consext, keallegulatryy impacts, accoomichurket factur, techncallppentioon details, ethical considentions, cuiturl implications, geogaphickomppuntee anilysis, stkeholldr persgectives, issi//iimtationss Coverage eanging yet purposeful; simply presening 3. Support
debate insutiienn inrelvant tungents avoided.
""Decriptio.."" "* Evalmate the coport's evidence and the quality and integration sources. Providing a reference list or in-line citations with UKLs is the provided,
manimum requirement: if verifiable clains clearyy and accuntally attrihused veriflblee sources (egg. paes-reviewed articles, government datalasees reputibii news organizations) proper citations. (2) Quaniiative data is presented with conteat, including the source. time frame, and relevant comparative benchmarris. (3) Qualitazive anguments are suppocted by concrese, well explained esamples case studies, with their sources clearly cited. (4) Sources are credible and balanced: cherry-ickking data omitting ckady relevant counter-cvidenes penalized. report's synthesi should baild upan cited restate
must
For higher
All factual assertions. data, signiscant
just
6, Readability
""Descripiin"" Assess the report's clarity, organization, and profesionalism in iss writing and piesentation. A highly rendable repoct easy to understan stan and follew, with clear topic sentences, formatting slements ideas logical, with smooth transtioons between points, paragmahi and sections. Converslly a report with poer readability is difficutt to follow. It may characterized by long, complex sentences, large blocks of dense text 'wals of test's ), vague umbiguuus language, and frequent grammatical or spelling disorganized semettree incoherest flow enstre the report's content occessible target audiesee
professoonal lmnguage avoiding unnecessary jurgon defining upon first Paragraphs logically stractured effectively gaide
headings. suhbeadings,
up text.
incomiiteatt poorly designed visual aids diminish readabilryy The ulimate gool message comaraticuted effectively.
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F COST ANALYSIS
Cost analysis. We provide a detailed cost analysis Table 9. We must first note that wall-clock times are highly sensitive to external factors like API latency, network conditions, and concurrent GPU capabilities (8 H20 GPU), As our experiments were conducted under resource-constrained academic conditions, the reported times should be viewed as a practical reference rather than an absolute benchmark metric. With that context, Web Weaver with Claude-sonnet-4 spends more wall-clock time (e.g., ~29 min and S2.82 per task on DeepResearch Bench) compared with the strong baseline 1enpiii-25--rr-ddereeeeee
This higher cost is a direct consequence of its comprehensive evidence gathering, which enables the high-quality reports for writing.
To provide a more efficient alternative, our fine-tuned model, Qwen3-30b-a3b. drastically reduces latency for planning and writing. Notably, the total end-to-end time (~118 min on DeepResearch Bench) is highly competitive with the Gemini baseline's estimated generation time (~16 min). This demonstrates that our framework is both practical and efficient even under academic research constraints. We have included detailed discussions about costs in the revised manuscript.
Planner
Writer
Search API
Input token
Outpat token
Time
Input token
Output
Time
Money of Google LLM
Search
SeraperAPI
DeepResearch Bench
Gemini-2.5 --ppre-2---poodeeresachhhh
16
Web Weaver
(Claude 4-205555--20
196,808
10,298
13.4min
522,765
33,653
15.6
2.825
WebWeaver (0wen3-30b-a3b)
163,510
8,447
11.8min
564,676
36,619
6.0 min
16.65
110.23
DeepConsult
Gemini 2.5 deenesearch
14 min
WebWeaver
(0aud=-sommet442225555144 188,084 WebWeaver
9045
12.5min
471,929
29,525
14.8 min
2.568
17.91
109. 86
(Qwen3-30b a3b)
151,381
7933
10.1min
504,406
28,825
5.4 min
12.8
106.65
DeepResearch Gym
Gemini 2.5-pro- pro-deereeaarch
WebWeaver (Claud-somee:422255111 176,907
8511
12.2min
504,341
33,698
14.4
2.67S
21.93
102.55
WebWeaver
(Qwen3-300) a3b)
117,091
6767
9.3min
587,60
8876602 34,786 5.1 min
13.5
102
Table 9: Cost analysis of different agent systems. The money costs (S) are computed based on OpenRouter pricing. The wall-clock time for Gemini-2.5-pp -ariiii-.---rr-deeeressaael are manually measured from the Gemini web interface and represent the time for the final report generation. The token and money costs are unknown for Gemini-2.5- prrp---------ddeepeearcchh
DeepRaveerch Banch
Des DeepStassarchGym
Kouad:
70
53
53
breach
supprt
Broadt
Depert
Evaluation Metrics
Evaluation Metrics
Figure 13: LLM-judged scores for varying rounds of outline optimization on Deepresearch Bench.
Figure 14: LLM-judged scores for varying rounds of outline optimization on Deepresearch- Gym.
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G OUTLINE JUDGEMENT
LLM judgement for varying rounds outllies. To directly evaluate whether our optimization truly improves outline quality, we utilized an LLM-as-a-judge (Zheng et al., 2023) assess the outlines from each of the three optimization rounds using 1pp-441-mini-2225--444 following, depth, balance, breadth, support, and insightfulness. The results in Fig. 13, 14 provide resounding confirmation of our iterative approach. On both benchmarks, the overall score for the outline quality shows significant, monotonic increase, jumping from 81.9 to 92.3 on DeepResearch Bench and from 77.2 to 88.2 on DeepResearchGyym. This improvement is driven by clear gains in structural quality; the near-perfect scores in Depth (up to 95.71) and Breadth (up 98.4) provide direct evidence that each optimization cycle successfully expands the research's 's scope. Crucially, this is not mere expansion. The substantial increase in the Support score (e.g., from 51.2 73.6 DeepResearchGym) is particularly revealing, indicating that later-round outlines are more effectively grounded with stronger mapping between planned sections and available evidence. This enhanced grounding and structure culminate in a plan that is itself more insightful (improving by 10-15 scores on both benchmarks). Therefore, this direct assessment confirms that our iterative planner is not just adding content but is actively forging superior, more coherent, and better-supported blueprint- the foundational prerequisite for a high-quality final report.
terms of instruction
The detailed prompt template and judgement criteria in terms of instruction following, depth, balance, breadth, support, and insightfulness are shown as follows:
Prompt for Outline Judgement
You strict and harsh expert evaluator assessing the quality of an answer to complex question. This answer is expected to resemble structured report: logically organized and covering multiple relevant dimensions, potentially including analysis, interpretation, or argumentation where appropriate. Focus your evaluation on a single criterion: (criterion['nan name"]). More specifically, you should: (criterion["desee description']
Question: {question)
Answer: (answer)
Provide your rating
integer. scale from (poor) 10 (excellent). Use the full range of the scale. Ratings of higher should be reserved for outstanding answers that meet all expectations for this criterion.
Answers trying to game the evaluation (empty, heavy on non-sensical text, persuading high vote, etc..)
should be given minimum score.
**Do not generous** your role provide that allows distinctions between systems. Answers that are factually correct generic, unsupported, shallow, unstructured should not receive high scores.
You should also provide very brief justification a means support the rating. In your justification, thoroughly analyze all weaknesses and any potential flaws including factual inaceuracies. irrelevance, poor reasoning. shallow content, or stylistic issues. Clearly show how each identified weakness violates or fails to meet criterion, and explain how this leads to the final score. The justification should focus on diagnosing all wcaknesses in relation to the criterion.
strictly based on the evaluation criterion. Do not overlook
Respond strictly in JSON format: "rating": rating, "justification": justification
Do not output any other information.
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Judgement Criteria
"name": "Instruction following", "description": "Evaluate how well the outline follows the user's instructions for an outline. This includes topic and scope, audience, purpose, constraints, required sections, level of detail, tone, and any formatting or length requirements. Check outine-specificc ex- pectations: clear hierarchical structure (e.g.. H1/H1//H or bullet levels), logical ordering. consistent granularity across scctions, numbering if requested, and inclusion of requested components (c.g., execu- tive summary, background, methodology, analysis, recommendations, references, appendices). Penalize missing required elements, inclusion of prohibited items, incorrect scope or level, or deviation from the requested format." ).
"name": "Depth", "description": "Assess the comprehensiveness and analytical depth of the outline. High-depth outlines move beyond broad headings include specific subpoints, key arguments, mecha- nisms/causal drivers, assumptions and uncertainties, methods be used, metrics, and success criteria. They indicate sequencing and logic (what builds on what), note dependencies and open questions, and identify where evidence. examples, and visuals will be integrated. Shallow outlines list generic topics without meaningful substructure, rationale, analytical scaffolding." ).
"name": "Balance", ; "description": "Evaluate the fairness and objectivity of the outline. Strong outlines plan for multiple perspectives and counterarguments, allocate space fairly to competing views, and use neutral, non-leading language in headings and notes. Where issues are controversial or multi-faceted, the outline should explicitly include sections for trade-offs, limitations, and counter-evidence. Poor outlines display bias, give disproportionate space to side without justification, or omit salient opposing views."
"name": "Breadth", "description": "Evaluate how many distinct and relevant subtopics, perspectives, or contexts the outline covers, while staying focused on the brief. Excellent outlines include appropriate dimensions such historical context, legal/regulatory, cconomic/market. technical/operational. ethical, social/cultural, geographic/comparrtive. stakeholder analysis, risks/limitations, and implementation pathways. Coverage should wide-ranging yet purposeful: simply presenting two sides a debate insufficient, and irrelevant tangents should be avoided."" ),
""name:: "Support". "description". "Evaluate the outline's evidentiary scaffolding and sourcing plan. Providing source URLs somewhere in the outline (e.g.. references section or inline citations) is the minimum: if no section provides source URLs, the score must zero. Factual accuracy necessary not sufficient. For higher scores: (1) Any factual assertions or planned claims are explicitly attributed to verifiable sources (pecr-reviewed articles, government databases, reputable news organizations) with traccable citations (author/outlet, date, URL). Vague references like "studies show" unacceptable. (2) Quantitative points specify precise datasets reports, time frames, and comparative benchmarks be used. (3) Qualitative points identify concrete examples or case studies include, clearly linked to the argument, with sources. (4) Sources are credible and balanced; cherry-picking or omission of clearly relevant counter-evidence. is penalized. Original synthesis should build on the cited material, not replace it."
"name": "Insightfulnesss. "description": "Assess how insightful and practically useful outline is. Excellent outlines go heyond common templates, offering original structure or framing, highlight- ing non-obvious but relevant connections, and sequencing sections to surface key insights efficiently. Recommendations and proposed analyses concrete and actionable, indicating what will be done, where it will appear, and how outcomes will be measured. Strong outlines call out specific real-world examples or comparator cases (who what, when, outcomes observed, how measured) and propose suitable exhibits (lables, charts, frameworks) with a clear purpose. Vague, generic, or purely aspirational notes cannot score highly."
H LIMITATIONS
Dependence on High-Capability Foundational Models. The performance of the WebWeaver framework is intrinsically tied to the capabilities its underlying LLM. The Open-Ended Deep Research (OEDR) task demands sophisticated, multi-turn tool-calling over extended contexts, high bar for agentic reasoning that many off-the-shelf models currently fail to meet. Consequently, our work necessitated the use of a powerful proprietary model for high-quality data generation and a relatively large, 30B-parameter model for our fine-tuned agent. While our SFT experiments successfully demonstrate that these complex skills can be transferred, we acknowledge that 30B model still represents a significant computational barrier to widespread adoption. A critical avenue for future work is therefore to explore advanced techniques aimed at cascading these expert capabilities onto smaller, more accessible models, thereby fully democratizing high- reggpperffrmaccc autonomous research.
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1 PROMPTS AND CASE STUDIES
1.1 PROMPT FOR URL SELECTION
Prompt for URL selection
Please process the following search results and user goal to extract all relevant urls:
**Search Results** beearchrresuly
U*eeser *oal** [goal]
**aak Guidelines
1. **Content Scanning for Rational**; Locate all the relevant **urls** directly related to the user's
goal according the titles, snippets, and url format in the search content.
**Extract relevant urls goals**; Identify and extract all the **ceevannt urls** from the content, you never miss any important urls, output the **full original urls** of the content as far as possible. Ensure the urls are valid and complete.
**Final Output Format using ISON format has "rational", "urls" feilds** Output example: "'json( "rational": "The rational is..." " "urls": ["urll", "url2", "url3"]
1.2 PROMPT FOR SUMMARY AND EVIDENCE EXTRACTION
Prompt for Summary and Evidence Extraction
Please process the following webpage content and user goal extract relevant information:
**Webpage Content** twehpage_content
**User Goal** (goal}
**Taask Guidelines
1. **Content Scamning for Rational**: Locate the **specific sections/data** directly related to the user's goal within the webpage content
""Key Extraction for Evidence**; Identify and extract the **most relevant information from the content, you
to maintain details much as possible, output the **full original context** of content as far as possible, can more than three paragraphs.
should maintain the important
original tables and diagrams.
3. **Smmaary Output for Summary** Organize into concise paragraph with logical flow, prioritizing clarity and judge the contribution of the information the goal.
#+ninal Output Format using JSON format has "rational". "evidence". "summary" feilds
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1.3 REACT TRAJECTORIES
Our ReAct framework is implemented through Qwen-Agent A complete trajectory of planning follows the format below:
Case Trajectory of Planning
<think> Analyze what content has been got, what other content are needed, think how to improve the outline for the query </think>
<tool_call>
I"name": "tool name here". "arguments": ("parameter name here": parameter value here, "another parameter name here": another parameter value here....]
Sttol_caals>
stool_responser
tool response here
</tool response>
<think Analyze what can be included into the outline the query </think>
<write outline> write the outline here </write outline>, Must end with </write outline>_
(more thinking processes, tool calls, tool responses and write here)
<think> Analyze what content has been got, what other content are needed, and think how to improve the outline for the query </think> <terminate> the writing process is terminated.
complete trajectory writing follows the format below:
Case Trajectory of Writing
<think> thinking which tool needed here </think>
<tool_call>
("name": "tool name here", "arguments": ("parameter name here": parameter value here, "another parameter name here": another parameter value here....)) ...
Sttoo_calls
<tool_ reol_resspnse>>
tool response here
rrooo_respons>>>>
<think thinking what content can be utilized to answer the query here </think>
<write> write the section paragraph here </write> (more thinking processes, tool calls, tool responses
write here)
<terminate> the writing process is terminated.
'https:/ //g thub. com www..//w///./eee.oo..oc hwtp///eennnnnnneeee
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1.4
PROMPT OF PLANNER
Prompt of Planner
A conversation between User and Assistant. The user asks for comprchensive, logical, insightful outline given topie, and the assistant assembles step-by-step by invoking the tools and iteratively output outline of deepreasearch report. The assistant should consider the following factors: 1. Thinking: Think about how to gather all the necessary information to enrich the outline using the search tool. Think about and search the causes and reasons for the core questions of the topic until producing comprehensive and insightful outline.
Search and visit: Search and Visit to retrieve all relevant information for the topic. Do visit the same webpage twice.
3. Search content: Search the comprehensive content, underlying causes, and its implications for the topic.
4. Writing and updating outline:
After getting some information beyond the exsiting outline from searching and visiting, update (add remove sections) and reorganize the outline to make logical, insightful, and comprehensive to the query.
S. If there some citations missing in the subsection in the outline, search for more information to verify the outline, and then update the outline in the next cycle.
Outline structure: Build a clear, hicrarchical structure (c.g., I. A. 1. a.) that covers all essential facets of the subject and follows the requirements of question. Only output the section or subsection title in the outline. The hicrarchy should be detailed up to the level four (c.g.. 1.1. The generation and update of the outline must be ended with <write <write_outling _otttiiee_.....
Outline citations: Ensure the source <id> cite after each subsection, with format: subsection <citation> <id_ 1>, <id 2>, ....ttciaaion>. Keep the cited the strictly same as the original ids. those subsections without citations, search for more information and update the outline in the next cycle. 8. Outline update: At least update and reorganize the outline with three times. For those subsections with similar content, merge them into one by combining the citations.
Outline content: Besides the phenomenon and hasic analysis, facus more the insightful reasoning and divergent thinking to enrich the outline. Include insights, reasoning, and analysis into the any sections and subsection if necessary.
10. Outlie structure: Each section should include the analysis, causes, impacts, and solutions if necessary. Ensure the logical flow of the outline is easy-understanding, clear, and logical.
11. Output format: Use lags for oulput: <ehini>> processes</think,, <tool call>tool Bile/tool_call>> rooo_response>too response content responssss,sss>,,,, <write_ wwrite_outlinne-utiin con- <terminate>
<tools>
"name": "search".
"description": "Perform Google web searches, select related pages, visit them and output relevant statements for the query. Accepts multiple queries.",
"parameters": I
"type": "object".
"properties":
"query": { "arra""
"array",
"items": "type": "string" ).
"description": "Array of query strings. Include multiple complementary search queries in single call." 1.
"goal": [
"type": "string", "description": "The specific information goal for searching and visiting webpage(s)."
"required": "qquery" "goal") ] }}
</tools>
The assistant starts with one or more cycles of (thinking about what content to he searched -> performing tool call >> waiting for tool response -> write the outline), and ends with <terminate>. The thinking processes, tool calls, tool responses, writting content, and terminate signal are enclosed within their tags. There could be multiple thinking processes, tool calls, tool call parameters tool response parameters.
Example response: (Trajectory of Planning]
User:
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1.5
PROMPT OF WRITER
Prompt of Writer
conversation between User and Assistant. The user asks question, and the assistant follows the outline to write a long report or article by calling the tool and writing every section and paragraph. The assistant should follow the sources provided in outline to retrieve related information for writing. If no sources are provided, the assistant should collect information from <material> section. The article should be as detailed as possible. <tools>
"name": "retrieve",
description": "Read the webpage(s) whose id matches the given id and return the summary.",
"parameters": {
"type": "object",
"properties":
"url_id":
"type": ["string". "array",,
"items":
"type": "string" 1.
"minltems":
"description": "The URL ID(s) of the webpage(s) to visit. Can be single URL ID) or an array of URL IDs.")
"goal":
"type": "string",
"description": "The goal of the visit for webpage(s))"
} }.
"required": "url_id", "goal" </tools>
We have explored some subqueries related to the query "[query)". To write a comprehensive and informative article on this topic, we also provide url id, title, and some statements with corresponding evidence related to the query and the subqueries. Please write a comprehensive and informative article for the query based on the provided information. The collected materials are as follows:
<material>
(Summary)
</material>
You must strictly follow the outline and fill in the contents.
<outline>
{outline)
</outline>
User query: (query)
The assistant starts with one or more cycles of (thinking about which tool to use -s performing tool call waiting for tool response -> thinking what content can be utilized answer the query -> write the section or paragraph), and ends with <terminate>. The thinking processes, tool calls. tool responses, writting content, and terminate signal are enclosed within their tags. There could be multiple thinking processes, tool calls, tool call parameters and tool response parameters.
Example response: (Trajectory of Writing)
User:
I.6 CASE STUDY OF PLANNING
Case Trajectory of Planning in DeepResearch Bench
Question: Parkinson's 's disease has a profound impact on patients. What are the potential health warning signs associated with different stages of the disease? As family members, which specific signs should alert us to intervene or seek medical advice regarding the patient's condition? Furthermore, for patients who have undergone Deep Brain Stimulation
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(DBS) surgery, what daily life adjustments and support strategies be implemented to improve their comfort and overall well-being?
Step 1
<think>
This is a comprehensive query about Parkinson's 's disease that requires detailed information
multiple aspects:
1. Health warning signs at different stages of Parkinson's 's disease
Specific signs that should alert family members to seek medical intervention
3. Daily life adjustments and support strategies for patients who have undergone DBS surgery
I need to gather information systematically about:
The stages of Parkinson's 's disease and their characteristic symptoms
Early warning signs and progression indicators
Red flag symptoms that require immediate medical attention
-BBS surgery outcomes and post-operative care
Daily living strategies and support systems for DBS patients
Let me start by searching for information about Parkinson's 's disease stages and warning signs. </think>
<tool_call>
I"name": "search", "arguments": I"query": ["Parkinson's disease stages symptoms warning signs", "carly signs Parkinson's disease progression". "Parkinson's disease Hochn and Yahr stages"]. "goal": "Gather comprchensive information about the different stages of Parkinson's s disease and their associated warning signs and symptoms")
</tool_call>
rtooo_respons>>>
<material>
<id_l>
Parkinson's disease progresses through five defined stages: Stage 1 shows mild, unilateral tremor with minimal impact on daily life; Stage adds bilateral tremor, rigidity, and noticeable gait/posture changes, making tasks harder; Stage 3 introduces balance problems, frequent falls, and slowed movements, requiring assistance with dressing, eating, and bathing: Stage 4 features severe motor impairment needing walkers or caregiver help, ending independent living; Stage 5 is the most advanced, with inability to walk, bedridden status, and possible cognitive disturbances. Early warning signs include a subtle tremor (often starting in a finger), nhirr-handwritingg stiffness, and facial masking, which gradually intensify-tremor spreading, rigidity, shuffling gait, swallowing difficulties, and speech changes-mirroring the stage-by-stage deterioration.
Summary:
</id 1>
responsess
Step 2
<think>
Great! I've gathered comprehensive information about Parkinson's disease stages and warning signs. Now need to search for specific information about: Red flag symptoms that should alert family members to seek immediate medical intervention
2. Deep Brain Stimulation (DBS) surgery and post-operative care
3. Daily life adjustments and support strategies for DBS patients
Let search for information about emergency warning signs and when family members should seek immediate medical help. </think>
<tool_call>
("name": "search". "arguments": ("query": ["Parkinson's disease emergency warning signs family caregivers", "when to call doctor Parkinson's 's disease red flags". "Parkinson's disease complications requiring immediate medical attention"]. "goal": "Find specific warning signs
26

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Published as a conference paper at ICLR 2026
and emergency situations that should prompt family members seek immediate medical intervention for Parkinson's 's patients")
</tool_ealll
stool_responte
<material>
<id_5.
Summary:
Parkinson's 's disease begins with subtle, often unilateral signs such barely noticeable tremor, slight stiffness, slowed movements (bradykinesia), reduced facial expression, and diminished arm swing- these constitute the early stage. As the condition progresses, symptoms become bilateral and more pronounced, including persistent tremor, rigid muscles, poor posture, balance problems, loss of automatic movements, speech and writing changes, and a range of non-motor issues (depression, anxiety, constipation, sleep disturbances, olfactory loss, fatigue). In later stages, complications emerge: cognitive decline and dementia, emotional changes, swallowing and chewing difficulties, severe sleep disorders, autonomic dysfunction (bladder urgency, orthostatic hypotension), chronic pain, and sexual dysfunction. Overall, the disease follows trajectory from mild, often unnoticed early warnings to widespread motor and non-motor impairments that intensify over time.
</id_5>
Step 3
<think>
Excellent! now have comprehensive information about warning signs and emergency situations for family members. Now I need search for information specifically about Deep Brain Stimulation (DBS) surgery, post-operative care, and daily life adjustments for DBS patients.
</think>
<tvol call>
("name": "search", "arguments": ("query": ["Deep Brain Stimulation DBS Parkinson's post-operative care", "DBS surgery recovery daily life adjustments Parkinson's s", "living with DBS Parkinson's disease support strategies"], "goal": "Gather detailed information about Deep Brain Stimulation (DBS) surgery outcomes, post-operative care requirements, and daily life adjustments needed for Parkinson's patients who have undergone DBS"))
</tool_ <clol_
<tool response>
<material>
<id_38>
Summary:
DBS surgery offers significant benefits for Parkinson patients, helping manage movement disorders and enhance quality of life when combined with proper post-operative care and follow-up. Patients receive comprehensive support-including recovery and safety guides, FAQs, and detailed manuals- through Boston Scientific's DBS system, and can obtain personalized assistance from a DBS Care Specialist during business hours. </id 38>
@iooo_ressponee
Step 4
<think>
Now I have good information about DBS surgery and post-operative care. Let me search for more specific information about daily life support strategies, comfort measures, and family caregiver guidance for DBS patients.
</think>
<tool eall>
1 I"name": "search". "arguments": ["DBS patient daily living support family caregivers",
"Parkinson DBS lifestyle modifications comfort strategies", "DBS programming adjustment
27

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Published as a conference paper at ICLR 2026
patient family guide"), "goal": "Find specific daily life support strategies, comfort measures, and family guidance for caring for Parkinson's patients who have undergone DBS surgery" |
<tool_ rrooo_rsspons>>
<material>
<id_54
Summary:
Deep-brain stimulation reliably improves motor symptoms in Parkinson's disease for at least five years, but the rapid symptom relief creates a "biographical disruption" that reshapes patients' daily lives and identities. The authors describe four-stage DBS pathway: pre-surgical decision making; the operation with required physical support and clinical goal-setting; post-operative changes in symptoms, behaviour and role dynamics; and finally re-engagement with life and future outlook. Post-operative care therefore extends beyond the surgical wound include structured psychosocial support-cconsellingg. triadic nurse-patient-spous meetings, and possibly nognitive-behavinn therapy-to help patients and partners negotiate new role boundaries, regain autonomy, and manage the "burden of normality" that can follow sudden functional gains. Daily-life adjustments reported by patients and spouses include shifting from a combined caregiver- pattiet identity more balanced spousal relationship, reclaiming personal interests, reducing wer-protecttvve behaviours, and actively addressing personal health and social needs. Pre- and post-DBS counseling, regular multidisciplinary follow-up. and interventions that foster positive psychology (e.g., character-strengle exercises) are recommended smooth these transitions and support long-term quality of life.
</id 54>
</tool_responeee
Step 5
<write outline>
Parkinson's ' Discase: Health Warning Signs, Family Alert Systems, and Post-DBS Care
Strategies
I. Understanding Parkinson's 's Disease Progression and Warning Signs
A. Disease Staging Systems
1. Hoehn and Yahr Scale Classifications <citation>id_2, id_6, id_ id_ id_13, id_14,
id 15, id_ 17, id id_20, id_21</cittiio>>>
Stage O: No detectable disease
Stage 1.0: Unilateral motor symptoms with minimal functional impact
Stage 1.5: Unilateral involvement with axial symptoms
Stage 2.0: Bilateral symptoms with preserved balance
Stage 2.5: Mild bilateral disease with normal pull-test recovery
Stage 3.0: Bilateral disease with postural instability but retained independence
g. Stage 4.0: Severe disability requiring assistance but can still walk/stand
h. Stage 5.0: Wheelchair-boule or bedridden without assistance
2. Movement Disorder Society- Unified Parkinson's Disease Rating Scale (MDS-
Ucitt)ccitatiooiid_ 3//ccitttiiiiiiinn>>
Four-domain assessment approach
b. Motor and non-motor impact evaluation Replacement for older staging systems
B. Early Stage Warning Signs (Stages 1-2)
Motor Symptoms <eitationzid. 2, id id_ 18, id 22</citation> a. Subtle unilateral tremor (often starting in finger)
Micrographia (small handwriting)
Bradykinesia (slowed movements)
Mild rigidity and stiffness
Reduced arm swing
Facial masking (reduced expression)
g. Shuffling gait with irregular stride
2. Non-Motor Early Indicators <citation>id_3 id_ id_7, id__I</citation>
28

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Published as a conference paper at ICLR 2026
Hyposmia (loss of smell)
b. Constipation
Sleep disturbances and REM sleep behavior disorder
d. Depression and anxiety
Subtle cognitive changes
f. Autonomic dysfunction (blood pressure fluctuations)
g. Unexplained weight loss
C. Progressive Stage Warning Signs (Stages 2-3)
Advancing Motor Symptoms <citation>id_5 5, id 6, _8, id 22</citation>
Bilateral tremor and rigidity
Postural deterioration and stooped posture
Balance problems and impaired reflexes
d. Speech changes (soft, monotone voice) Swallowing difficulties
f. Freezing episodes
Emerging Complications <eitationzid 16, id 18, id 22</citation> Medication wearing- off periods Levodopa-induced dyskinesia
Increased fall risk
Emotional and mood changes
D. Advanced Stage Warning Signs (Stages 4-5)
Severe Motor Impairment <citation>id_55 5, id_6, id_9, id_ 22</citation>> Major mobility loss requiring assistive devices
Severe postural deformities
Inability live independently
d. Wheelchair or bed confinement
Complex Non-Motor Complications <citaton>>>d id 16, id id__9, id 22<lcitation>
Cognitive decline and dementia
Hallucinations and delusions
Severe autonomic dysfunction
Chronic pain and sexual dysfunction
II. Critical Warning Signs Requiring Immediate Medical Intervention
A. Emergency Situations for Family Members
1. Respiratory and Swallowing Emergencies <citation>id 25, id 26, id 29, id 11, _2_
id 35_ od_36</citation>>
Sudden choking difficulty swallowing
b. Aspiration risk with coughing while eating
Severe voice changes stridor
d. Respiratory difficulty or shortness of breath
Neurological Crisis Signs <citation>id_ 22,idd__22______ id 26__26,111 id [d__28,14 id_32, id_33, id_35</eitation> Sudden confusion, delirium, or marked cognitive decline
New or worsening hallucinations, delusions, or paranoid thoughts Abrupt neurological deficits (weakness, speech changes) Loss of consciousness or seizures
3. Medication-Relan
Emergencies <citation>id_ satpsdddd__,,d1 [d__2,,4 id 3__3<</iitaton>>>
a. Abrupt stopping or alteration medications
b. Exposure to dopamine-blocking drugs
c. Missed or delayed essential medication doses
d. Signs of serotonin syndrome
B. Cardiovascular and Autonomic Emergencies
Cireulatory Complications <eitation>id_ 26, id 28_ id_31, id_32, id_34, id _d_36</eitation>>
Severe orthostatic hypotension causing fainting
Chest pain cardiac symptoms
Signs of blood clots (leg swelling, pain, redness)
Marked dehydration
2. Infection and Systemic Issues <citation>id 24, id id_26, id_32, id 35<///iiiation>>>
Sudden fever with respiratory or urinary symptoms
29

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Published as a conference paper at ICLR 2026
Signs of urinary tract infection
C. Post-surgical complications
d. Severe constipation or bowel impaction
C. Psychiatric and Behavioral Emergencies
Mental Health Crises <citation>id 28, id id_32, id 33, id id_36</citation>
Severe depression or suicidal thoughts
Violent behaviors during REM sleep disorder
Severe impulse-control behaviors
Acute psychosis with agitation or aggression
2. Device-Related Emergencies <citation>id 28, id 34_33//ciattio>>>>
a. Sudden malfunction of implanted devices
b. DBS system problems (infection, battery failure)
Unexpected sleep attacks during critical activities
III. Deep Brain Stimulation (DBS) Surgery: Comprehensive Care Framework
A. Pre-Operative Considerations and Evaluation
Candidate Selection Criteria <citation>id 45, id 56</citation>
Minimum four years of Parkinson's 's disease
Continued medication benefit with motor complications
Absence of dementia or severe cognitive impairment
Realistic expectations about outcomes
2. Pre-Surgical Assessment Process <citation>id_ ,9, id_45,,445 id 2d_56//citation>>>>
a. Multidisciplinary team evaluation
b. Neurological and neurosurgical consultation
c. Cognitive testing and brain imaging
d. Medication review and optimization
B. Surgical Procedure and Immediate Post-Operative Care
Surgical Process <citation>id 45, id id_49, id 51, id 56</citation>
a. Electrode implantation in target brain regions
Pulse generator placement under collarbone Brief hospital stay (1-2 days)
Low mortality rate (<0.5%) and modest complication rates (4-7%)
2. Initial Recovery Phase <citation>id_ _1,1__111111 id_47, id_499 id_51, id_52, id <516/eccttaioo>>>> Expected post-operative signs (bruising, swelling, tenderness)
b. Temporary "honeymoon" microlesion effect
c. Activity restrictions (4-6 weeks)
d. Wound care and infection prevention
C. Device Programming and Optimization
Programming Timeline <citation>id__4 (1,,__411111_0, id_4, id_46, id_47, id_51,11111 id_56</citationn>>>>>
a. Initial activation 2-4 weeks post-surgery
Optimization period of 4-6 months
Multiple programming visits required
Ongoing adjustments every 6 months
2. Expected Outcomes and Adjustments <citation>id 2_,,,4_6,640_ id_51, id_53, id id_56</citation>> Significant motor symptom improvement (= 32%)
b. Medication reduction (up 48%)
Functional independence gains
d. Possible side effects requiring management
IV. Daily Life Adjustments and Support Strategies for DBS Patients
A. Physical Care and Safety Measures
Activity Modifications <citation>id 47, id_51, i2_ id_ id <7</ciiiinn
Gradual resumption of normal activities
b. Continued use of mobility aids to prevent falls
Avoidance of high-risk activities (deep water diving, extreme heat)
d. Regular exercise program (minimum 2.5 hours weekly)
Device Safety and Maintenance <citationzid 51, id 52, id 69</citation>
Protection from electromagnetic interference
Carrying handheld controller at times
30

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Published as a conference paper at ICLR 2026
Informing healthcare providers about implanted device
d. Regular battery monitoring and replacement
B. Psychosocial Support and Adaptation
1. Identity and Role Adjustment <citation>id_5 _4, id 66, id (6<<citaaion>>> Managing "biographical disruption" from rapid symptom relief
caregiver-patient b. Negotiating new caregiver patient role boundaries
Addressing "burden normality" phenomenon
d. Reclaiming personal interests and autonomy
Family Relationship Dynamics <citation>id 54, id 58, id 66, id 68</citation>> Shifting from caregiver-pationn to balanced spousal relationships
Reducing over-protectivy behaviors
Open communication about changing abilities
d. Professional counseling and cognitive-bchavioaal therapy
C. Comprehensive Support Systems
Healthcare Team Coordination <citation>id_99 id_46, id_61, id_72</ciattion>
Multidisciplinary follow-up care
b. Specialized Parkinson's nurses
Home-health nursing services
d. Telemedicine and remote programming options
Family and Caregiver Support <citation>id 58, id_66, 61, id_63, id_66, id 68</citation> Pre-operative education and realistic expectation setting
Structured psychosocial interventions
Self-help groups and peer support networks
Caregiver self-care and stress management
D. Practical Daily Living Strategies
Routine and Symptom Management <citation>id_ id_65, id_67<letattion> Structured daily routines and symptom diaries
b. Medication schedule adherence
Regular physical activity (walking, tai chi, dancing)
d. Comfort measures (leg massages, voice training)
Nutritional and Lifestyle Support <ciattionsid_64</ciaatooo 67</citation>>
Mediterranean diet implementation
Adequate rest and sleep hygiene
Intellectual activities and cognitive stimulation
Consultation with specialized healthcare providers E. Long-term Monitoring and Adjustment
Ongoing Assessment Needs <citation>idd 47, id_52, (d</c/citttion>>
Regular follow-up visits (monthly for first six months)
b. Symptom tracking and device optimization
Monitoring for complications or side effects
d. Battery replacement planning (every 3-5 years)
Quality of Life Optimization <citation>id 51. id 54, id 61</citation>
Patient satisfaction monitoring (95% would recommend DBS)
Positive psychology interventions
Sharacter-strengee exercises
Long-term relationship and social support maintenance
</write_outline outline>
Step 6
<think>
have now created a comprehensive outline covering all aspects of the user's query. The
outline includes:
Detailed information about Parkinson's 's disease stages and warning signs at each stage Specific emergency warning signs that should alert family members seek immediate medical intervention
Comprehensive information about DBS surgery, including pre-operative considerations, surgical process, and post-operative care
Detailed daily life adjustments and support strategies for DBS patients
31

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Published as a conference paper at ICLR 2026
The outline is well-structured with proper hierarchical organization and includes citations from the research materials. However, should search for any additional information that might be missing, particularly around specific comfort measures and practical tips for families caring for DBS patients. </think>
<tool_call>
("name": "search". "arguments": ("query": ["Parkinson DBS patient comfort measures home care tips", "DBS device troubleshooting family guide", "Parkinson DBS medication manage- ment post surgery"], "goal": "Find additional specific comfort measures, troubleshooting guidance, and medication management strategies for families caring for DBS patients")
e/tool_calls
<tool reso_rrsssss>>
<id_65>
Summary:
The guide provides comprehensive daily-life support for Parkinson's 's patients after DBS: keep incisions clean, dry, and allow them heal without ointments; shower the day after surgery but avoid baths/swimming until the wound check. Resume Parkinson's 's meds immediately and discuss timing for blood-thinner restart. Limit strenuous activity for 2-4 weeks and incorporate gentle neck stretches to prevent bow-stringing. Expect DBS activation about 4 weeks post-stage and be patient with programming adjustments. Anticipate possible temporary confusion-maiitaiin walking, and good sleep (melatonin if needed); arrange caregiver assistance especially living alone. Monitor for fever, worsening incision signs, facial swelling, neurological deficits, or worsening confusion, and contact the surgeon promptly. These strategies together offer practical comfort measures and clear family guidance for post-DBS care.
consistent routine, strict medication schedule, regular
</id 65>
</tool response>
Step 7
<write_outhigg outline>>>>
Parkinson's 's Disease: Health Warning Signs, Family Alert Systems, and Post-DBS Care
Strategies
I. Understanding Parkinson's Disease Progression and Warning Signs
A. Disease Staging Systems
1. Hoehn and Yahr Scale Classifications <citation>id 2, id 6, id 9, id 12, id 13, id 14,
id 15, id 17, id 20, 21</citation>
Stage O: No detectable disease
Stage 1.0: Unilateral motor symptoms with minimal functional impact
Stage 1.5: Unilateral involvement with axial symptoms
d. Stage 2.0: Bilateral symptoms with preserved balance
Stage 2.5: Mild bilateral disease with normal pull-test recovery
Stage 3.0: Bilateral disease with postural instability but retained independence
g. Stage 4.0: Severe disability requiring assistance but still walk/stand
h. Stage 5.0: Wheelchair-bound or bedridden without assistance
2. Movement Disorder Society- Unified Parkinson's Disease Rating Scale (MDS-
Xcittixcitatio>iid X 3</citation>
Four-domain assessment approach
b. Motor and non-motor impact evaluation
Replacement for older staging systems
3. Disease Progression Timeline and Transition Indicators <citation>id _16 id 17,
id_ 19</citation>>>
Median transition times between stages (20-26 months)
HY > as critical threshold for advanced disease
Shift from dopaminergic cortical pathology involvement
B. Farly Stage Warning Signs (Stages 1-2)
Motor Symptoms <citation>id id_5, id ii__118,, id 22</citation>
a. Subtle unilateral tremor (often starting in finger)
32

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Published as a conference paper at ICLR 2026
Micrographia (small handwriting)
Bradykinesia (slowed movements)
Mild rigidity and stiffiess
Reduced arm swing
Facial masking (reduced expression)
Shuffling gait with irregular stride
Non-Motor Early Indicators <citation>id_3, id_5,,,, id_7, id_I8</citation>
Hyposmia (loss of smell)
Constipation
Sleep disturbances and REM sleep behavior disorder
Depression and anxiety
Subtle cognitive changes
f. Autonomic dysfunction (blood pressure fluctuations)
g. Unexplained weight loss
3. Diagnostic Challenges and Recognition
Non-mon con-motor signs can appear decades before motor symptoms
b. Overlap with other disorders complicates diagnosis
Need for asymmetric symptoms or medication response for confirmation
C. Progressive Stage Warning Signs (Stages 2-3)
Advancing Motor Symptoms <citation>id_5 id 6, id__d_11111 id 22</citation>
Bilateral tremor and rigidity
Postural deterioration and stooped posture
Balance problems and impaired reflexes
d. Speech changes (soft, monotone voice) Swallowing difficulties
f. Freezing episodes
Emerging Complications <citation>id 16, id__i811___ 18, id 22</citation>
a. Medication wearing-ofe off periods
Levodopa-inducee dyskinesia
Increased fall risk
Emotional and mood changes
3. Functional Impact Assessment <citation>id_6. 6, id_20, id 2d_2<</citation>>>>>
Loss of independence in daily activities
b. Need for assistance with dressing, eating, bathing
c. Occupational and social limitations
D. Advanced Stage Warning Signs (Stages 4-5)
Severe Motor Impairment <citation>id 5, id_6, id_9, id 22</citation> Major mobility loss requiring assistive devices
b. Severe postural deformities Inability live independently
d. Wheelchair or bed confinement
Complex Non-Motor Complications <citation>id id 16, id 19, id 22</citation>
Cognitive decline and dementia
Hallucinations and delusions
Severe autonomic dysfunction
Chronic pain and sexual dysfunction
3. End-Stage Considerations <citation>id 6, 9, id 20</citation>
a. Complete dependency for daily activities
b. Risk of aspiration and respiratory complications
c. Need for constant supervision and care
II. Critical Warning Signs Requiring Immediate Medical Intervention
A. Emergency Situations for Family Members
Respiratory and Swallowing Emergencies <citation>id_2 id 26, id 29, id, id_
id. 35, id_36</citation>>
Sudden choking or difficulty swallowing
b. Aspiration risk with coughing while eating
Severe voice changes or stridor
33

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Published as a conference paper at ICLR 2026
d. Respiratory difficulty shortness of breath
2. Neurological Crisis Signs <citation>id 24, id__6,2________ id 28, id__2, id_3dd33333___3 id_33</citation>>
Sudden confusion, delirium, or marked cognitive decline
b. New or worsening hallucinations, delusions, or paranoid thoughts Abrupt neurological deficits (weakness, speech changes)
d. Loss of consciousness or seizures
Medication-Rede Emergencies <citation>id_22 id_28, id_33</citation>
Abrupt stopping or alteration of medications
Exposure to dopamine- blocking drugs
Missed or delayed essential medication doses
d. Signs of serotonin syndrome
4. Motor System Crisis <citation>id, 25, id id_28, id_31, id 3<</ciitationn>
a. Sudden severe rigidity or immobility
Frequent falls freezing episodes
c. Rapid loss of walking ability
Severe dyskinesia with complications
B. Cardiovascular and Autonomic Emergencies
Cireulatory Complications <citationzid 26, id id_28, id_31, id_32, id_34, id_ /L_36c/citatio>>>
Severe orthostatic hypotension causing fainting
Chest pain or cardiac symptoms
Signs of blood clots (leg swelling, pain, redness)
Marked dehydration
2. Infection and Systemic Issues <citation>id 24, id 26, id id_32, id 35</citation>>
a. Sudden fever with respiratory or urinary symptoms
Signs of urinary tract infection
c. Post-surgical complications
d. Severe constipation or bowel impaction
C. Psychiatric and Behavioral Emergencies
Mental Health Crises <citation>id, 28, id_32, id 33, id_ 3_///ciitttion>>>>
Severe depression or suicidal thoughts
Violent behaviors during REM sleep disorder
Severe impulse-control behaviors
Acute psychosis with agitation or aggression
2. Device-Relaane Emergencies <citation>id 28, id 34</citation>
a. Sudden malfunction of implanted devices
DBS system problems (infection, battery failure)
c. Unexpected sleep attacks during critical activities
D. Hospitalization and Perioperative Risks <citation>id_33 id_55//citationn
1. Hospital-Related Complications
Medication timing disruptions
b. Delirium and confusion in unfamiliar environments
Increased fall risk and injury potential
d. Aspiration pneumonia during procedures
Post-Surgical Warning Signs
Rapid symptom deterioration
Signs of infection or wound complications
Unexpected neuropsychiatric changes
III. Deep Brain Stimulation (DBS) Surgery: Comprehensive Care Framework
A. Pre-Ope Pre-Operative Considerations and Evaluation
Candidate Selection Criteria <citation>id 45, id_56</citation>
Minimum four years of Parkinson's 's disease
b. Continued medication benefit with motor complications
Absence of dementia or severe cognitive impairment
d. Realistic expectations about outcomes
Pre-Suree Pre-Surgical Assessment Process <citation>id 39, id 45, id 56</citation>
Multidisciplinary team evaluation
Neurological and neurosurgical consultation
34

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Published as a conference paper at ICLR 2026
Cognitive testing and brain imaging
d. Medication review and optimization
Target Selection Considerations <citation>id 53</citation>
Subthalamic nucleus (STN) for greater medication reduction
Globus pallidus interna (GPi) for language/cognition preservation Individual patient factors influencing choice
B. Surgical Procedure and Immediate Post-Operan Operatvee Care
1. Surgical Process <citation>id_44 45, id_49, id_51, id <0_56</citation>>
a. Electrode implantation in target brain regions
b. Pulse generator placement under collarbone
c. Brief hospital stay (1-2 days)
d. Low mortality rate (<0.5%) and modest complication rates (4-7%)
2. Initial Recovery Phase <citation>id_ _1, id_47, id_499 id_51, id_52, id_65</citation> Expected post-operative signs (bruising, swelling, tenderness)
b. Temporary "honeymoon" or microlesion effect Activity restrictions (4-6 weeks)
d. Wound care and infection prevention
Early Post-Operative Monitoring <citation>id_66 id 8888///iittiin>>> Incision care and healing assessment
Medication resumption protocols
Activity limitation guidelines
Signs requiring immediate medical attention
C. Device Programming and Optimization
Programming Timeline <citation>id _1,, id_45,,115 46, id_47, id_ id_ 16_/</cctttiion>>
Initial activation 2-4 weeks post-surgery
Optimization period of 4-6 months
Multiple programming visits required
d. Ongoing adjustments every 6 months
Expected Outcomes and Adjustments <citationzid 46, id_51, id__ddd__33._. id_ 56</citaiion Significant motor symptom improvement (= 32%)
Medication reduction (up 48%)
Functional independence gains
Possible side effects requiring management
3. Programming Process and Patient Education <citation>id 80, id 86, id 90</citation>
a. cntirnt-controlled adjustments with handheld programmer
b. Battery monitoring and replacement scheduling
c. Understanding normal sensations vs. concerning symptoms
Communication protocols with programming team
IV. Daily Life Adjustments and Support Strategies for DBS Patients
A. Physical Care and Safety Measures
1. Activity Modifications <citation>id 47, id 51, _d_ id_65, id 67</cittaionn>
Gradual resumption normal activities
b. Continued use of mobility aids prevent falls
Avoidance of high-risk activities (deep water diving, extreme heat)
d. Regular exercise program (minimum 2.5 hours weekly)
Device Safety and Maintenance <citation>id 51, id_ 52, 69, id_ id 88<lcitation> Protection from electromagnetic interference
Carrying handheld controller at all times
Informing healthcare providers about implanted device
d. Regular battery monitoring and replacement
3. Environmental Safety Considerations <eitation>id_ _88, id 90//citatiion>>>>>
Contraindicated therapies and equipment
Safe vs. unsafe daily activities
Travel and security considerations
Workplace and recreational restrictions
B. Medication Management Post-DBS
Immediate Post-Operative Medication Protocol <citation>id_ 84, id_88, id 93</citattion
35

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Published as a conference paper at ICLR 2026
Continuation of pre-surgical regimen initially
b. Gradual, systematic reduction approach
Monitoring for withdrawal symptoms
d. Coordination with stimulation programming
Long-Teme -erg-Term Medication Optimization <citation>id_.. 83, id id_84, id_85, id 93</citation>>
Levodopa dosing adjustments
Dopamine agonist tapering strategies
Management of persistent symptoms
Monitoring for mood and cognitive changes
3. Troubleshooting Medication Issues <eitationzid 81, id 86</citation>
a. Home-health nurse medication reviews
b. Emergency protocols for medication disruption
c. Balancing stimulation with pharmaceutical needs Communication with neurology team
C. Home-Based Care and Comfort Measures
Daily Routine Optimization <citation>id 63, id 66, id_67, id 72</citation> Structured daily routines and symptom diaries
Sleep hygiene and rest protocols
Regular physical activity programs
Comfort interventions (massage, voice training)
2.
Home Health Services <citation>id 72, id 81</citation>>
a.
Trained home-health nurse visits
b. Remote programming capabilities
c. Vital sign monitoring and medication adjustments
d. Reduced travel burden for families
3. Device Troubleshooting at Home <citation>id_77, id_78, id_86, id id_9O</citation>
Basic device operation and monitoring
b. Recognition of malfunction signs
Emergency contact protocols
d. Battery status management
D. Psychosocial Support and Adaptation
1. Identity and Role Adjustment <citation>id_ __4, id_66, id_ 1886</ciitaion>>>>>>
a. Managing "biographical disruption" from rapid symptom relief
b. Negotiating caregiver- patient role boundaries
c. Addressing "burden normality" phenomenon
d. Reclaiming personal interests and autonomy
2. Family Relationship Dynamics <citation>id __0,,,dd_,,,___ id_58, id_ id_66, id (88//ciitation>>> Shifting from caregiver-pation
balanced spousal relationships
b. Reducing over-protective behaviors
Open communication about changing abilities
d. Professional counseling and cognitive-behavioral
behavioral therapy
Caregiver Support and Education <citation>id 61, id 66, id 68<lcitation>
Pre-operative education and expectation setting
Structured psychosocial interventions
Self-help groups and peer support networks
Caregiver self-care and stress management E. Comprehensive Support Systems
Healthcare Team Coordination <citation>id id__d__,,4 46, id_61, id_ 72</citation>>
Multidisciplinary follow-up care
b. Specialized Parkinson's nurses
Home-health nursing services
d. Telemedicine and remote programming options
Long-Tem -Tem Quality of Life Optimization <citation>id 55, id 54, id 61</citatio>>>
Patient satisfaction monitoring (95% would recommend DBS)
Positive psychology interventions
Character-strength exercises
Long-term relationship and social support maintenance
36

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Published as a conference paper at ICLR 2026
3. Emergency Preparedness and End-of-Litf Considerations <citationsiid78</cttaano
Off-trial protocols for device assessment
Palliative care coordination
Hardware monitoring in advanced stages
Family decision-makeen support
F. Practical Implementation Strategies
Daily Living Skills <citation>id _60, id_63, id_67<<citation>>
Gradual re-engagement in routine tasks
Nutritional support (Mediterrancan diet)
Intellectual and social activities
d. Family encouragement and participation
2. Long-term Monitoring and Adjustment <citationzid 47, id_52, id 69</citation>>
a. Regular follow-up visits (monthly for first six months)
Symptom tracking and device optimization
c. Monitoring for complications or side effects
d. Battery replacement planning (every 3-5 years)
3. Resource Utilization and Support Networks <citation>id 55, id id_58, 76_76
id_ 79</citation>>
Educational materials and patient guides
Webinars and professional consultations
Support groups and peer networks Specialized healthcare provider access </write outline> -write-
Step 8
<think>
1 have now created a comprehensive, detailed outline that addresses all aspects of the user's
query. The outline includes:
1. Detailed Parkinson's disease staging and progression with comprehensive warning signs
Specific emergency situations requiring immediate medical intervention
3. Complete DBS surgery information including pre-operative, operative, and post-operative
care
4. Extensive daily life adjustments and support strategies for DBS patients
Proper citations for all subsections
The outline is well-structured with four levels hierarchy and covers all essential aspects requested. It provides practical, actionable information for families caring for Parkinson's 's patients, particularly those who have undergone DBS surgery. The outline is comprehensive, logically organized, and includes insights into the reasoning behind various care strategies.
I believe this outline now fully addresses the user's comprehensive query about Parkinson's disease warning signs, family alert systems, and post-DBS care strategies. </think>
<terminate> V
1.7 CASE STUDY OF WRITING
We present only the first steps of the long writing trajectory to save space. The afterwards reasoning process is similar to that in the first steps.
Case Trajectory of Writing in DeepResearch Bench
Question: Parkinson's s disease has a profound impact on patients. What are the potential health warning signs associated with different stages of the disease? As family members, which specific signs should alert us to intervene or seek medical advice regarding the patient's condition? Furthermore, for patients who have undergone Deep Brain Stimulation
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(DBS) surgery, what daily life adjustments and support strategies be implemented to improve their comfort and overall well-being?
Step 1
<think>
need to write a comprehensive article about Parkinson's 's disease warning signs, emergency situations for family members, and post-DBS strategies. Looking at the outline, should start by retrieving information about disease staging systems and warning signs. Let me begin with the first section on understanding Parkinson's 's disease progression and warning signs. </think>
<tool call>
("name": "retrieve", "arguments": ["url_id": ["id_2] 2", "id_6", "id_9", "id_12", "id_13" "id_14" 14", "id_ "id_15", "id_17 17", "id_20", "id [i"_ "goal": "Gather comprehensive information about Hochn and Yahr scale classifications and discase staging systems for Parkinson's disease"]]
</tool_call>
<tool_ reooorrsssss>>>>
The page content for the previous section has been masked for saving the space. <esoo__rssposs>>>
Step 2
<think>
have comprehensive information about the Hochn and Yahr scale classifications and disease staging systems. This provides solid foundation for understanding Parkinson's 's disease progression. can see the clear progression from Stage O (no disease) through Stage (wheelchair/bedridden)) with intermediate stages 1.5 and 2.5 in the modified version. The information shows both motor and non-motor symptoms, timing of transitions between stages, and functional impacts. should now write the takeaway section and begin the first major section on disease staging systems. </think>
<write>
<takeaway>
Parkinson's 's disease progresses through distinct stages with recognizable warning signs that families must understand to provide appropriate care and seek timely medical intervention. The disease advances from subtle unilateral symptoms in early stages to severe bilateral impairment requiring constant care in advanced stages. Critical emergency signs include sudden choking, severe falls, medication disruptions, neurological changes, and psychiatric crises that demand immediate medical attention. For patients who have undergone Deep Brain Stimulation (DBS) surgery, comprehensive daily life adjustments encompass structured post-operative care, medication management, device safety protocols, psychosocial support, and coordinated family involvement to optimize comfort and long-term outcomes. Understanding these progressive warning signs and implementing evidence- support strategies enables families navigate the complex challenges of Parkinson's disease while maintaining patient dignity and quality of life.
</takeawa>>
Parkinson's Disease: Health Warning Signs, Family Alert Systems, and Post-DBS Care
Strategies
I. Understanding Parkinson's Disease Progression and Warning Signs
A. Disease Staging Systems
Understanding Parkinson's 's disease progression requires familiarity with established staging systems that provide frameworks for recognizing symptom evolution and functional decline. These systems
critical tools for families understand what to expect and when to seek medical intervention.
Hoehn and Yahr Scale Classifications
The Hoehn and Yahr scale, originally published in 1967, remains the most widely used system for staging Parkinson's disease progression. <eite id="id 14.id 17">This scale distinguishes between five stages of Parkinson's 's Disease, from unilateral impairment (Stage to bilateral impairment, without postural control difficulties (Stage 2), to postural instability
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(Stage 3), loss of physical independence (Stage 4) and finally, wheelchair-bound bed-bound (Stage 5)/ccite> The modified version includes intermediate stages that capture more nuanced progression patterns. <table>
<caption>Hoehn and Yahr Scale Progression and Warning Signs</caption>
<thead>
<tr>
<th>Stage</th>
<th>Primary Characteristics<thh>
<th>Fuunciooal Impact</th>
<th>Key Warning Signs for Families</th>
</tr>
</thead>
<tbody>
<tr>
<td>Stage 0</td>
<td><cite id="id 12.id >1">No signs of diseuse</cite></tt>
<td>Normal function</td>
<td>Baseline monitoring period</td>
</tr>
<tr>
<Id>Stage 1.0</td>
<td><cite id="id_ 15,id 20*>Unilateral tremor, rigidity, reduced arm swing, and slowness
present only on one side</cite></tt>>
<td><cite id="id_2,id "e_id_6""MMin 6'>MMinaall interference with daily activities</cite><hhb>
<td>Subtle tremor in one finger, asymmetric arm swing</hd>
</tr>
<tr>
<td>Stage 1.5</td>
<td><cite id="id_ 15,id 21 Ulnlatrlatrrr involvement with axial symptoms like reduced facial expression, stooped posture, or reduced arm swing on both sides</cit>></t>> <ld>Slight postural changes</td>
<td>Facial masking, posture changes visible family</td>
</t>>
<tr>
<td>Stage 2.0</td>
<td><cette id="id_ 13.la_rl" involvement without impairment of bal-
ance</<ite><<tt>>
<id><cite (d="id_2.id_ 2.id_6">Daily activities become more difficult but independent living realistio</cit>></tb>>
<td>Tremor and stiffness on both sides, speech difficulties</td> </tr>
<tr>
<td>Stage 2.5</dd>
<id><cite id="id_ _5,i__,dd____ 2il>Mild bilateral disease with recovery pull test (taking >3 steps to recover balance)</cite><<(t>>>>>>>
<td>Mild balance impairment</dd>
<td>Slight unsteadiness, requires multiple steps to recover balance</td>
</t>> <tr> <td>Stage 3.0</t>>
<id><cite id="id__3..0 1i___1,ddd20""'_0" 20">Mild to moderate bilateral disease with impaired postural reflexes; physically independeent//ciee>chhd
<id><cite id="id 2.id 6">Falls become frequent, assistance needed for some activi- lies</eite></d>> <id>Loss of balance when pulled backward, increased fall risk</td> </t>> <tr> <td>Stage 4.0</td>
<td><cite id="id 13,id 20">Severe disability; still able walk or stand unassisted but markedly incapacitate<</cie>e/hdd
<id><eite id='id_2.id Boadd6""CCaa Cannot live independently, requires walker or assis-
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tance</cite><</tb>> <td>Need for assistive devices, inability to live alone safely</td> </tr> <tr> <id>Stage 5.0</t>>
<id><cite id="id 13.id Wheecherl bound bedridden unless aided</cite><ltt> <td><cite id="id_ 2,id 6""AAronn-thhe-llo nursing care required, up to 50% experience
hallucinations and delusions<<cii>></db>>>>>
<id>inability to stand or walk, cognitive disturbances, complete dependencyc/td> </tr>
</tbody> </table>
This staging system reveals several critical insights for families. **The transition from Stage 2 to Stage 3 marks pivotal point** where balance problems emerge, fundamentally changing the patient's s safety profile and care needs. <cite id="id_20">loos Los= of balance, with the inability make the rapid, automatic and involuntary movements necessary to protect against falling, is one of the most troubling and dangerous aspects of Parkinsonism and one of the least easily treated</cite>. Understanding this progression helps families anticipate when environmental modifications and increased supervision become essential.
*Thhe distinction between Stage and Stage centers on independence** id="id 20e>The most important factor identifying Stage III (as opposed to stage IV) is that patient is still fully independent in activities of daily living (dressing, hygiene, eating, etc.), while Stage IV patients are unable to lead an independent life because of the need for help with some activities of daily living</cite>, This transition signals when families must consider more intensive caregiving arrangements assisted living options. </write>
<cite
Step 3
<think>
Now need to continue with information about the MDS-UPDRS system and disease progression timeline. Let me retrieve more specific information about these aspects.
</think>
<tool_call>
("name": "search", "arguments": ("url_id) ["id_3", "id_16", "id_17", "id_ 19"], "goal":
"Gather information about MDS-UPDRS assessment system, disease progression timeline, and transition indicators between stages")]
</tool call>
<tool response>
The page content for the previous section has been masked for saving the space.
Step 4
<think>
The tool response provides valuable information about the MDS-UPDRS system, disease progression timeline, and the critical transition point at Stage 3. can see that:
has replaced the older Hoehn- Yahr system the main assessment tool 2. The progression timeline shows median transition times between stages (20-26 months typically)
1.
3. Stage 3 (HY 3) represents critical threshold marking advanced disease with increased
disability, pedication-refractton features, and cognitive decline
4. There's 's important information about non-motor symptoms appearing years before motor symptoms
5. Specific progression warning signs are detailed
I should continue writing about the MDS-UPDRS system and progression timeline, then move on to early stage warning signs. </think>
<tool <all>
I ("name": "scarch", "arguments": ["DBS patient daily living support family caregivers", "Parkinson DBS lifestyle modifications comfort strategies", "DBS programming adjustment
patient family guide"), "goal": "Find specific daily life support strategies, comfort measures, and family guidance for caring for Parkinson's patients who have undergone DBS surgery" </tool_calls
<write>
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2. Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) While the Hoehn and Yahr scale remains valuable for understanding disease progression, <cite id="id 3">the Movement Disorder Society-Unified Parkinson's Disease Rating Scale IMDS-UPDRS) is healthcare providers' main tool to classify this disease. The MDS-UPDRS examines four different areas of how Parkinson's 's disease affects you</cite>. This comprehensive assessment tool provides more nuanced evaluation of both motor and non-motor symptoms, addressing the limitations of purely stage-based approaches.
** significance of this shift toward individualized assessment cannot be overstated** Rather than simply categorizing patients into stages, the MDS-UPDRS recognizes that Parkinson's disease affects each person differently, requiring personalized treatment approaches. This evolution in assessment methodology reflects our growing understanding that the disease's 's impact extends far beyond motor symptoms.
3. Disease Progression Timeline and Transition Indicators
Understanding the temporal aspects of Parkinson's progression helps families prepare for changing care needs. <cite ad= Med>Me transition times between stages show Stage progression occurring around 20 months, with subsequent stages progressing every 24-26 months</cite>. However, <cite id="id "ae"ddd_""""""""""""""""" 16">for some people, it can take as long as 20 years to move through all the stages</cite>, emphasizing the highly variable nature of disease progression.
** transition to Stage 3 represents a critical threshold** in Parkinson'ss 's disease progression. <cite (d="idd_I">Tiii T from scores of <2.5 to scores of 23 on the modified HY scale mark a worsening in quality of life and an increase in the risk disease features such dementia and mortality</cite>. This transition point signals when families must significantly intensify their care planning and support strategies. The underlying pathophysiology also changes this critical juncture. <cite "a="id_19>AAtiiii
medication-refractur
striatal dopaminergic neuropathology accounts for many of the early motor features of PD, vivo imaging studies suggest floor effects to striatal dopaminergic denervation that occur both in early PD and at HY stage disease, at which point progressive disease burden driven by other factors</cite>. This shift from primarily dopaminergic to multi-system pathology explains why treatment becomes more complex and why families observe new types of symptoms emerging.
B. Early Stage Warning Signs (Stages 1-2)
Early recognition of Parkinson's 's disease symptoms enables timely medical intervention and better long-term outcomes. The challenge for families lies in distinguishing between normal aging changes and early disease manifestations.
1. Motor Symptoms
The classic motor symptoms of Parkinson's disease typically appear gradually and asymmetrically. <cite [d="idd3">MMtor symptoms which means movement-related symptoms - of Parkinson's disease include tremor at rest, bradykinesia (slowness of movement), rigidity (muscle stiffness), and postural instability (balance problems)</cite>. **Tremor characteristics provide important diagnostic clues** The typical Parkinson's 's tremor occurs at rest, often beginning subtly in one finger or hand. Families should note that this tremor typically diminishes during purposeful movement, distinguishing it from other Syriicattttmmmtosss beginning on
types of tremors. The asymmetric onset particularly one side of the body more suggestive of Parkinson's disease than bilateral symptoms. ** **Bradykinsiaa manifests multiple ways* that families can observe daily activities.
This slowness of movement affects not only gross motor activities but also fine motor skills, leading to characteristic changes in handwriting (micrographia). reduced facial expression (facial masking), and decreased arm swing during walking. These changes often develop so gradually that they may be attributed to normal aging until they become more pronounced. **Rigidity and postural changes** represent another category of early motor symptoms. Families may notice increased muscle stiffness, particularly in the neck and shoulders, leading to complaints of aching or discomfort. The development of stooped posture and reduced arm swing during walking are early indicators that warrant medical evaluation. Non-Motor Early Indicators
Perhaps most significantly for early detection, <cite id="id 3">many of the possible non-motor symptoms can appear years or even decades ahead of motor symptoms<dcite>.
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This extended prodromal period offers families crucial opportunities for early intervention, though the subtlety of these symptoms often leads to delayed recognition.
**Olfactory dysfunction represents one of the earliest detectable changes* <cite id="id_3">Loss of sense of smell (anosmia)</cite> occurs in approximately 90% of Parkinson's s patients, often years before motor symptoms appear. Families should take note when a loved one reports that food no longer tastes the same or when they fail to detect strong odors that others notice readily.
**Gastrointestiaal symptoms, particularly constipation**, frequently precede motor Parkinson's disease results from the same pathological processes affecting the brain, specifically involving the enteric nervous system. This symptom is often dismissed as age-related or dietary, but persistent constipation without clear cause warrants medical attention.
symptoms by years. <cite id="id_ id="idd3" < S"sSCostipatiion/ciiee
**Sleep disturbances provide another early warning system**, <cite id="id_3""> "id__""appppd eye movement sleep behavior disorder</cite> is particularly significant, it involves acting out dreams during sleep, potentially including violent movements or vocalizations. <cite id="id 16" REM sleep behavior disorder can also happen in people who don't have Parkinson's s. However, if this isn't I something you' ve dealt with before, it's likely related to your disease<</cte>>. Family members sharing bed are often the first to notice these changes. **Neurossychiaric symptoms deserve particular attention*** from families. <cite id="id_33 "">iidd""Dersriiooo or anxiety</cite> can appear years before motor symptoms, and <eite id="id >nxxieyy and depression have been linked to Parkinson's 'ss In addition to movement problems, the disease can also have an impact on your mental health<<cite>> These mood changes may be subtle initially but can significantly impact quality of life and relationships. </write>
Step 5
<think>
Now I need to continue with information about progressive stage warning signs and advanced stage warning signs. Let me retrieve more specific information about these later stages and their complications.
</think>
<tool <all>
{ I"name": "retrieve", "arguments": ("url_de id": ["id_5", "id 6", "id_18", [d_]. "goal": "Gather detailed information about progressive and advanced stage warning signs, including motor and non-motor complications").
</tool call>
<tool_ree rroo_srespsse>>>>
The page content for the previous section has been masked for saving the space.
</tool response>
Step 6
<think>
The tool response provides excellent detailed information about progressive and advanced stage warning signs. can clear patterns in the progression from mild moderate to advanced stages, with specific motor and non-motor symptoms at each stage. The information shows how symptoms evolve from unilateral bilateral, how functional independence is progressively lost, and how non-motor symptoms become increasingly prominent and disabling. I should organize this information to show the progression clearly and highlight the key warning signs families need to recognize. </think>
<write>
C. Progressive Stage Warning Signs (Stages 2-3)
As Parkinson's 's disease advances beyond the carly stage, families observe more pronounced symptoms that begin to significantly impact daily functioning. This progressive phase represents critical period where proactive intervention can substantially influence quality of life outcomes.
Advancing Motor Symptoms
**e bilateral spread of symptoms marks a fundamental shift** in disease progression.
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<cite id="id_18"s" As the disease progresses, it eventually affects both sides. However, the symptoms may still be more severe on one side than on the other</cite>. This bilateral involvement signals that families must adapt their support strategies address more comprehensive functional limitations.
<eite id="id 22">Often within 3 to years, you'll see more changes. Early on, you might have little trouble with something like buttoning a shirt. At this point, you may not be able to do at all</cite>, **This progression from mild difficulty to complete inability** represents pattern families will observe across multiple daily activities, requiring gradual assumption of caregiving responsibilities.
**Speech and swallowing changes become particularly noticeable** during this stage. <cite id="id_5's "0"55""Yo may speak softly or quickly, slur, or hesitate before talking. Your speech may be flat monotone, without typical speech patterns</cite>. These changes affect not only communication but also safety, as <cite id="id_22" "troubbe swallowing</cite> increases the risk of aspiration and nutritional deficiencies.
**Gait disturbances and freezing episodes** represent some of the most challenging aspects of progressive Parkinson's disease. <cite id="id 18" >People with Parkinson's 's disease often develop parkinsonian gait that includes tendency to lean forward; take small, quick steps; and reduce swinging their arms. They also may have trouble initiating or continuing movement</cite>. The emergence of <cite id="id_ _0_222" 22">freezing when you first start to walk or change direction, as if your feet are glued to the ground</cite> creates significant safety concerns and mobility limitations.
Emerging Complications
*Medication effectiveness begins to fluctuate** during the progressive stage, creating new challenges for symptom management. <cite id="id "0" You might also find that the medicine you take starts wear off between doses</cite>, This "wearing-off" phenomenon requires families to become more attentive to timing of medications and to recognize when symptoms return between doses.
**allace problems and fall risk increase substamtially** <cite id="id "a""dd_""""" 6">At this stage, falls become more frequent due balance and reflex problemsc/cite>, and <eite id="id >f">falls to be more likely</cite>. This increased fall risk necessitates environmental modifications and potentially the introduction of assistive devices. 3. Functional Impact Assessment
**The distinction between Stages and 3 centers on independence preservation <cite id="id 6" 6">>ue to the various issues this stage presents, daily tasks much more difficult to do, but people can still live independently. A combination of medication and therapy can help manage the symptoms mentioned above</cite>. Understanding this threshold helps families recognize when to increase support while still encouraging independence.
D. Advanced Stage Warning Signs (Stages 4-5)
The advanced stages of Parkinson's disease present complex challenges that require comprehensive care planning and family coordination. These stages are characterized by severe functional limitations and the emergence of complications that significantly impact quality of life.
1. Severe Motor Impairment
*Saage marks the loss of independent living capability <cite (d="id_6">>Te critical factor in separating people with stage 3 Parkinson's 's and stage is independence. Motor skills and deep brain stimulation are heavily impacted at stage and as such, movement symptoms affect person's ability retain their independence</cit>>. This transition requires families to make difficult decisions about living arrangements and care provision.
<cite id="id >2">At this point, you likely: Are limited to bed wheelchair, Can't live your own, Have severe posture issues in your neck, back, and hips, Need help with daily tasks</cite>. **The comprehensive nature of these limitations** means that families must coordinate multiple aspects of care, from basic hygiene to mobility assistance.
**Stage represents the most severe * of motor symptoms. <eite "a''idd'""SSeerr"" stiffness can make it difficult, if not impossible, for person to stand or walk. This is due stiffness causing the legs essentially freeze when the patient attempts to stand</cite>. This "freezing" phenomenon at the advanced stage differs qualitatively from earlier freezing episodes, representing more permanent limitation rather than intermittent
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diffieulty.
2. Complex Non-Motor Complications
**Cognitive decline becomes prominent feature** in advanced stages. <cite id="id_18">Over 18">Over time, as the disease progresses, some people may develop demen- tia and be diagnosed with Parkinson's 's dementia, type of Lewy body dementia. People with Parkinson's s dementia may have severe memory and thinking problems that affect daily living</cites. This cognitive impairment adds another layer of complexity to caregiving responsibilities.
**Psychiatric symptoms emerge as significant challenges**, <cite id="id F'r up to 50% of Parkinson's 's patients in stages and 5 experience confusion, hallucinationss, and delusions. For clarity, hallucinations are seeing things that aren't really there, and delusions are when a person believes something despite evidence the contrary</cite>. These symptoms can be particularly distressing for families and may require specialized psychiatric intervention.
**Swallowing and nutritional complications* become life-threatening concerns. <cite id="id S">Late-stage Parkinson's disease affects the muscles the mouth. This causes trouble swallowing and chewing, which can lead to not getting enough nutrients in your diet. food or saliva collects in the mouth, can cause choking or drooling</cites. These complications require careful monitoring and may necessitate alternative feeding methods. <table>
<caption>PProrressvve Warning Signs by Discase Stage</caption>
<thead> <tr> <th>Stage</th>
<th>Motor Warning Signs</th>
<tht-No-MMotor Warning Signs</th>
<th>suucttional Impact</th>
<th>Family Action Required</th> </t </thead> <thody> <tr> <ld>Early (1-2)</td>
<td>tnilateral tremor, mild rigidity, reduced arm swing, micrographia</dd>
<td>Sleep disturbances, constipation, loss of smell, mood changes</td> <td>Minimal daily life disruption</td>
<id>Medical evaluation, symptom monitoring</td>> </tr> <ld>Progressive (2-3)</td>
<id>Bilateral symptoms, gait freezing, speech changes, balance problems</td> <td>Medication wea cognitive changes, swallowing difficulty</td> Increccedd difficulty with daily tasks, still independent</td>
<td>>nvironmenza modifications, fall prevention, medication timing</td>
</tr> <tr> Advanndd (4-5)</t>>
<ld>Severe rigidity, wheelchair/bed bound, postural deformities</td>
<dd>Dementia, hallucinations, severe dysphagia, autonomic failure</td> <d>Complete dependency for daily activities</td>
hour care, safety monitoring, end-of plamnin<//t>>
</tr>
</tbody>
</table>
** temporal progression of non-motor symptoms** follows predictable pattern that families should understand. <eite id="id_22"">ii"" >2h> may show up early. You may have these issues years before any classic motor symptoms like tremors: Constipation, Depression, Loss of smell, Low blood pressure when you stand up, Pain, Sleep issues</cite>. Conversely, <cite id="id >2">What may show up later. Dementia and psychosis are two serious mental health issues that usually take a while to show up</cite>.
This progression pattern reveals that **non-motor symptoms often become disabling than motor symptoms*** in advanced stages. <cite id="id 22">Almost everyone with Parkinson's gets least one of these. When severe, they' 're more likely than motor issues to lead to disability or make you move into nursing home</cite>. This insight helps families understand why comprehensive care planning must address both motor and non-motor aspects of the disease.
End-Stage Considerations
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**hhe advanced stage requires families confront difficult realities** about prognosis and care goals. <cite id="id 22">After about 10 years, most people will have at least one major issue, like dementia a physical disability</cite>. Understanding this timeline helps families engage in advance care planning while the patient can still participate in decision- decision-making. "*The variability in progression ** means that some individuals may never reach the most severe stages, while others progress more rapidly. <cite id="id "is="idd2">SSS 2o_m2"m""mmeeeee people never reach this stage</cite> of advanced disability, emphasizing the importance individualized care planning rather than assuming inevitable decline. </write>
Step 7
<think>
Now need to move on to the second major section about critical warning signs requiring immediate medical intervention. This is crucial information for families know when to seek emergency care. Let me retrieve information about emergency situations and warning signs. </think>
<tool_call>>
("name": "retrieve", "arguments": ["url id": [2id_24", 24", "id_25", "id_26 _4_26", "id_28", "id_29", "id_31" "id 3_"2"" "id_33", "id 33", "id_35", "id [id_,66], "goal": "Gather comprehensive information about emergency warning signs and situations that require immediate medical intervention for Parkinson's patients")] </tool_call
<tool response>
The page content for the previous section has been masked for saving the space.
</tool response>
Step 8
<terminate> V
45


Reviews:
[{"review_id": "ulUilDdOwb", "reviewer": "Reviewer_21rJ", "summary": "The paper introduces WebWeaver, a dual-agent framework for open-ended deep research (OEDR).\nThe system consists of a Planner that dynamically do evidence acquisition and outline optimization, and a Writer that performs memory-grounded, hierarchical synthesis by section. The human-centric design simulates real research workflows.\nWebWeaver is claimed to achieve SOTA on DeepResearch Bench, DeepConsult, and DeepResearchGym against Gemini-2.5, OpenAI DeepResearch and Claude Research.", "questions": "see weakness.", "limitations": "", "rating": 8, "confidence": 4, "soundness": 4, "presentation": 4, "contribution": 3, "strengths": "- Clear and well-motivated problem framing: tackling OEDR beyond static pipelines.\n- Dual-agent design (Planner + Writer) inspired by real-wold human research process.\n- Extensive experiments across 3 major benchmarks with detailed breakdowns with strong quantitative evidence.\n- Thorough ablation and statistical analysis showing the strength of outline optimization and hierarchical writing.\n- Clear figures, intuitive workflow, and solid writing throughout.", "weaknesses": "- Heavy rely on LLM-as-judge evaluations that lacks human verification to some extend\n- I'm curious what's the computational cost and latency? \n- Some redundancy between Sections 3.2 and 3.3, the method flow could be slightly more concise.\n- How scalable is WebWeaver for real-world web-scale research (e.g., 1k+ page retrieval)?\n- How sensitive is performance to the backbone model (Qwen vs. Claude vs. GPT)?\n- Minor formatting issue: Fig. 1 move to page 2 looks better", "quality": null, "clarity": null, "significance": null, "originality": null, "strengths_and_weaknesses": "", "was_revised": false, "final_justification": "", "rebuttal": "", "claims_and_evidence": "", "methods_and_evaluation_criteria": "", "theoretical_claims": "", "experimental_designs_or_analyses": "", "relation_to_broader_scientific_literature": "", "essential_references_not_discussed": "", "other_strengths_and_weaknesses": "", "other_comments_or_suggestions": "", "questions_for_authors": "", "summary_of_paper": "", "summary_of_recommendation": "", "technical_quality": "", "clarity_of_presentation": "", "potential_impact": "", "robotics_focus": "", "quality_of_limitations": "", "questions_for_rebuttal": "", "reasons_to_accept": "", "reasons_to_reject": "", "questions_to_authors": "", "extra_scores": {}}, {"review_id": "OV3AhDySAt", "reviewer": "Reviewer_4PPn", "summary": "The paper introduces **WebWeaver**, a dual‑agent system (Planner + Writer) for “open‑ended deep research” (OEDR). The Planner iteratively interleaves web search and outline optimisation; the Writer then synthesises a long‑form report section‑by‑section using a citation‑grounded memory bank. The authors claim that this human‑inspired workflow eliminates the “loss‑in‑the‑middle” problem, reduces hallucinations, and yields state‑of‑the‑art results on three recently released OEDR benchmarks (DeepResearch Bench, DeepConsult, DeepResearchGym). They also present a 3 k‑example SFT dataset (WebWeaver‑3k) that purportedly enables a 30 B‑scale model to match the performance of much larger proprietary agents.", "questions": "1. Code/data release: Will you release the full WebWeaver code (planner/writer, tools, memory) and the WebWeaver-3k dataset? If not, what components will be made public and when?\n2. Fairness controls: Can you provide a controlled comparison where WebWeaver and a strong baseline agent both use the same backbone LLM and judge, to isolate framework gains? Any cross-judge robustness (e.g., alternate judges or human eval subsets)?\n3. Cost/latency: What are average wall-clock time, token counts, and dollar costs per task on each benchmark, for both planning and writing? How does it compare to baselines?\n4. Evidence extraction specifics: How are quote spans selected, how is evidence deduplicated/normalized, and what is the granularity for memory entries? How do you handle noisy, contradictory, or paywalled sources?\n5. Failure and correction: How do the planner/writer detect and correct citation errors (e.g., broken links, drifted IDs, semantically mismatched evidence)? Any automatic validation?\n6. WebWeaver-3k licensing and distribution: What is the licensing status of the dataset, given it is derived from web materials and proprietary teacher outputs? Can it be redistributed?\n7. Safety and misuse: What safeguards are in place to prevent the agent from citing low-quality or harmful sources? Do you filter by source credibility or domain allowlists/blacklists?\n8. Outline-to-retrieval mapping: How robust is the citation-ID mapping across multiple optimization rounds (IDs added/removed)? How do you maintain referential integrity?", "limitations": "", "rating": 6, "confidence": 4, "soundness": 3, "presentation": 3, "contribution": 3, "strengths": "- Clear, human-inspired, end-to-end system design with an explicit evidence chain: planning → evidence extraction into a memory bank → outline with citation IDs → retrieval-grounded writing. The qualitative case study is coherent and illustrates the intended workflow.\n- Across three reasonably comprehensive benchmarks, results indicate competitive to SOTA performance. On DeepResearch Bench, the reported citation accuracy (93.37%) and effective citations are particularly strong. On DeepConsult and DeepResearchGym, the win rate and average scores are strong relative to listed systems.\n- Ablations address two core hypotheses: (1) iterative outline optimization improves depth/breadth/support and end-to-end scores, and (2) hierarchical, citation-driven writing outperforms brute-force context stuffing. These analyses are aligned with the proposed mechanism of action.\n- Useful operational statistics (number of searches, outline size, number of saved pages, evidence tokens) convincingly argue that memory-centric, targeted retrieval is not just helpful but necessary under the reported scale (>100 pages, >60k evidence tokens).\n- The SFT dataset and fine-tuning experiments show that the framework can act as a data engine for transferring agentic skills to smaller models, with large gains in citation accuracy. This is a practical contribution for accessibility.", "weaknesses": "- Cost and budget parity are not controlled or reported. WebWeaver averages ~100+ pages parsed, ~67k evidence tokens, and ~26k-token outputs. Many baseline systems (especially proprietary) may have stricter rate/token limits. Without a controlled per-task budget (time, API calls, tokens), performance advantages may partly reflect higher spend rather than method.\n- Baseline comparability is unclear. WebWeaver is evaluated with multiple powerful base LLMs (Qwen-235B, Claude Sonnet 4), and even when the “agent model” is Claude, a separate model (GPT-oss-120B) is used for URL selection and evidence extraction. This multi-model, auxiliary-LLM design could materially boost performance yet is not mirrored for baselines. It is therefore difficult to isolate method gains from model capability/tooling differences.\n- Statistical analysis is thin. No confidence intervals, no statistical tests, and no repeated runs are reported. Improvements on RACE overall scores are modest versus strong baselines (e.g., ~1 point vs Gemini 2.5), and the absence of variance estimates undermines claims of reliable superiority. DeepConsult reports win/tie/lose counts but no significance testing despite pairwise comparisons being amenable to binomial or bootstrap CIs.\n- Reliance on LLM-as-judge across all benchmarks creates evaluation circularity risks; although the paper follows “official” judges per benchmark, additional human evaluation on a representative subset would strengthen claims, especially for “insight,” “readability,” and “support.”\n- Effective citations metric may be confounded by output length. WebWeaver outputs very long reports; if “Eff. c.” counts raw validated citations, longer outputs can inflate the score. There is no normalization for output length or per-claim basis reported. The very large Eff. c. numbers (200+) relative to baselines raise the possibility that the metric rewards verbosity rather than calibrated evidence use.\n- The ablation “hierarchical vs brute-force writing” lacks sufficient detail to be fully persuasive: context limits, chunking strategy for the brute-force baseline, and exact parity of planner outputs across conditions are not specified. Without these, it’s unclear if the baseline is disadvantaged by context overflow or suboptimal chunking rather than an inherent weakness of the paradigm.\n- The outline optimization ablation uses samples with three rounds of optimization and then evaluates earlier rounds; however, the prompt template prescribes “at least three” updates but the reported average outline optimization steps are ~2.2. This mismatch between prescribed behavior and observed behavior should be clarified.\n- No code, no executable release, and no links to run-time infrastructure are provided. Prompts are included, but the system depends on multiple LLMs, tools, and scraping steps. Critical parameters (stop criteria, deduplication policies, cache behavior, search engine settings, rate limits, tie-breaking rules, etc.) are not fully specified. This reduces reproducibility.\n- The WebWeaver-3k dataset creation lacks overlap analysis against evaluation prompts and lacks licensing audits of scraped content. Without an overlap/contamination check, the risk of implicit test exposure cannot be discounted.\n- The ethics section is a little generic at the moment and should also address website terms-of-service compliance, robots.txt adherence, or how PII in web pages is handled during evidence extraction and dataset curation. For an agent that crawls and stores web-scale evidence, these omissions are material.", "quality": null, "clarity": null, "significance": null, "originality": null, "strengths_and_weaknesses": "", "was_revised": false, "final_justification": "", "rebuttal": "", "claims_and_evidence": "", "methods_and_evaluation_criteria": "", "theoretical_claims": "", "experimental_designs_or_analyses": "", "relation_to_broader_scientific_literature": "", "essential_references_not_discussed": "", "other_strengths_and_weaknesses": "", "other_comments_or_suggestions": "", "questions_for_authors": "", "summary_of_paper": "", "summary_of_recommendation": "", "technical_quality": "", "clarity_of_presentation": "", "potential_impact": "", "robotics_focus": "", "quality_of_limitations": "", "questions_for_rebuttal": "", "reasons_to_accept": "", "reasons_to_reject": "", "questions_to_authors": "", "extra_scores": {}}, {"review_id": "wQQej1vPks", "reviewer": "Reviewer_yb9V", "summary": "The paper presents WebWeaver, a dual-agent system for deep research questions. They distinguish their approach from previous methods like “search-then-generate” or “outline-then-write”  by  introducing a planner–writer loop in which the planner iteratively refines a dynamic outline and the writer performs hierarchical writing. They run experiments on DeepResearch Bench, DeepConsult, and DeepResearchGym and showed they outperformed baselines.", "questions": "- Did you do any analysis on what actiona cause the most problem of answering wrong? for example things like early termination?\n-  how were the web queries for WebWeaver-3k crawled—were they topic-balanced or randomly collected?\n - How would webweaver as a dual agent do in terms of cost compared to single agent architechture", "limitations": "", "rating": 6, "confidence": 2, "soundness": 3, "presentation": 3, "contribution": 3, "strengths": "- The paper addresses an important and and timely problem.\n\n- The dual-agent design  is very tangible and human-inspired very well motivated.\n\n- Comprehensive experiments across three strong benchmarks\n\n- comprehensive ablation studies", "weaknesses": "- Missing cost analysis compared to baselines \nThe paper does not clearly specify when the planner decides to terminate the outline optimization process—what the stopping criteria or thresholds are.\n\n- Several important open-source baselines are missing, such as DeepResearcher, OpenScholar, and open sourced LLM + tool-use systems. Including these would strengthen claims of generality and fairness.\n\n- The WebWeaver-3k dataset is also said to be built from “diverse queries crawled from the web,” yet the crawling criteria, domains, or filters are unspecified.", "quality": null, "clarity": null, "significance": null, "originality": null, "strengths_and_weaknesses": "", "was_revised": false, "final_justification": "", "rebuttal": "", "claims_and_evidence": "", "methods_and_evaluation_criteria": "", "theoretical_claims": "", "experimental_designs_or_analyses": "", "relation_to_broader_scientific_literature": "", "essential_references_not_discussed": "", "other_strengths_and_weaknesses": "", "other_comments_or_suggestions": "", "questions_for_authors": "", "summary_of_paper": "", "summary_of_recommendation": "", "technical_quality": "", "clarity_of_presentation": "", "potential_impact": "", "robotics_focus": "", "quality_of_limitations": "", "questions_for_rebuttal": "", "reasons_to_accept": "", "reasons_to_reject": "", "questions_to_authors": "", "extra_scores": {}}, {"review_id": "r4UEVLUnpH", "reviewer": "Reviewer_W3Xh", "summary": "The paper proposes WebWeaver, a dual-agent “planner + writer” framework for open-ended deep research. The planner dynamically produces a structured outline with linked evidence; the writer then retrieves the required evidence section by section and composes the content hierarchically based on the outline. The authors conduct experiments and ablations across multiple benchmarks, and the results demonstrate the effectiveness of the approach.", "questions": "See weakness", "limitations": "", "rating": 6, "confidence": 4, "soundness": 3, "presentation": 3, "contribution": 3, "strengths": "1. The paper is easy to follow, the figures are clear, and the experimental details are thorough. The final results look solid.\n\n2. It folds “dynamic outline optimization + evidence binding” into the planning loop and uses section-wise retrieval + writing, which mirrors how humans actually do deep research.\n\n3. It releases a 3k SFT dataset and shows gains on smaller models, which supports the method’s effectiveness.", "weaknesses": "1. The planning stage parses 100+ pages and burns tens of thousands of tokens, but there’s no apples-to-apples report of wall-clock latency or API cost vs. baselines.\n2. It is recommended to include parameter-matched comparisons across different frameworks built on the same model backbone, or reproduction experiments against other strong baselines on the identical model.", "quality": null, "clarity": null, "significance": null, "originality": null, "strengths_and_weaknesses": "", "was_revised": false, "final_justification": "", "rebuttal": "", "claims_and_evidence": "", "methods_and_evaluation_criteria": "", "theoretical_claims": "", "experimental_designs_or_analyses": "", "relation_to_broader_scientific_literature": "", "essential_references_not_discussed": "", "other_strengths_and_weaknesses": "", "other_comments_or_suggestions": "", "questions_for_authors": "", "summary_of_paper": "", "summary_of_recommendation": "", "technical_quality": "", "clarity_of_presentation": "", "potential_impact": "", "robotics_focus": "", "quality_of_limitations": "", "questions_for_rebuttal": "", "reasons_to_accept": "", "reasons_to_reject": "", "questions_to_authors": "", "extra_scores": {}}]

Author rebuttal:

Decision: Accept (Poster)