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2410.19482 | 2024-10-30 | Measuring memorization through probabilistic discoverable extraction | [
"Jamie Hayes",
"Marika Swanberg",
"Harsh Chaudhari",
"Itay Yona",
"Ilia Shumailov"
] | null | null | 4 | 2 | 4 | 2024-10-30 | 2 | 4 | 4 | 4 | 0 | 4 | true | 2024-W44 | 2024-10 | false | 15 | 15 | 71 | 79 | 400 | 482 | Large language models (LLMs) are susceptible to memorizing training data,
raising concerns due to the potential extraction of sensitive information.
Current methods to measure memorization rates of LLMs, primarily discoverable
extraction (Carlini et al., 2022), rely on single-sequence greedy sampling,
potentially under... | [
{
"name": "Jamie Hayes",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Marika Swanberg",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Harsh Chaudhari",
"us... | null | null | null | iliashum | i | /avatars/757ed789423113369868e972f21ce559.svg | null | 2024-10-25T11:37:04.000Z | true | |
2512.07197 | 2025-12-10 | SUCCESS-GS: Survey of Compactness and Compression for Efficient Static and Dynamic Gaussian Splatting | [
"Seokhyun Youn",
"Soohyun Lee",
"Geonho Kim",
"Weeyoung Kwon",
"Sung-Ho Bae",
"Jihyong Oh"
] | https://github.com/CMLab-Korea/Awesome-Efficient-GS | https://cmlab-korea.github.io/Awesome-Efficient-GS/ | 8 | 2 | 8 | 2025-12-10 | 1 | 3 | 5 | 6 | 0 | 6 | true | 2025-W50 | 2025-12 | false | 14 | 27 | 78 | 130 | 407 | 633 | 3D Gaussian Splatting (3DGS) has emerged as a powerful explicit representation enabling real-time, high-fidelity 3D reconstruction and novel view synthesis. However, its practical use is hindered by the massive memory and computational demands required to store and render millions of Gaussians. These challenges become ... | [
{
"name": "Seokhyun Youn",
"user": "Seokhyun01",
"fullname": "Seokhyun Youn",
"avatar": "/avatars/3befa67c2bf7e9c3cb376f6b6f227242.svg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Soohyun Lee",
"user": null,
"fullname": null,
"avatar": null,
"status":... | null | null | null | ozbro | Jihyong Oh | /avatars/b533e776aa3d95d722b46ef0cd381acd.svg | 52 | 2025-12-08T06:15:59.000Z | true | |
2603.16669 | 2026-03-18 | Kinema4D: Kinematic 4D World Modeling for Spatiotemporal Embodied Simulation | [
"Mutian Xu",
"Tianbao Zhang",
"Tianqi Liu",
"Zhaoxi Chen",
"Xiaoguang Han",
"Ziwei Liu"
] | https://github.com/mutianxu/Kinema4D | https://mutianxu.github.io/Kinema4D-project-page/ | 47 | 4 | 70 | 2026-03-18 | 62 | 64 | 68 | 68 | 23 | 68 | true | 2026-W12 | 2026-03 | false | 7 | 52 | 20 | 194 | 58 | 745 | Simulating robot-world interactions is a cornerstone of Embodied AI. Recently, a few works have shown promise in leveraging video generations to transcend the rigid visual/physical constraints of traditional simulators. However, they primarily operate in 2D space or are guided by static environmental cues, ignoring the... | [
{
"name": "Mutian Xu",
"user": "Minoday",
"fullname": "Mutian Xu",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/64749a0d5aba8edfb2eeaba7/Tiy4DEdp3KQYh7Ij8Vmkn.png",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Tianbao Zhang",
"user": "ZTBob",... | mmlab-ntu | MMLab@NTU | yukangcao | Yukang Cao | 83 | 2026-03-17T15:36:38.000Z | true | |||
2410.20220 | 2024-10-29 | Neural Fields in Robotics: A Survey | [
"Muhammad Zubair Irshad",
"Mauro Comi",
"Yen-Chen Lin",
"Nick Heppert",
"Abhinav Valada",
"Rares Ambrus",
"Zsolt Kira",
"Jonathan Tremblay"
] | https://github.com/zubair-irshad/Awesome-Implicit-NeRF-Robotics | https://robonerf.github.io/ | 5 | 2 | 5 | 2024-10-29 | 3 | 4 | 4 | 4 | 0 | 4 | true | 2024-W44 | 2024-10 | false | 18 | 21 | 71 | 79 | 400 | 482 | Neural Fields have emerged as a transformative approach for 3D scene
representation in computer vision and robotics, enabling accurate inference of
geometry, 3D semantics, and dynamics from posed 2D data. Leveraging
differentiable rendering, Neural Fields encompass both continuous implicit and
explicit neural represent... | [
{
"name": "Muhammad Zubair Irshad",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Mauro Comi",
"user": "MauroC",
"fullname": "Mauro Comi",
"avatar": "/avatars/887d795e0e650a8cc67e66f552187a73.svg",
"status": "claimed_ver... | null | null | null | mirshad7 | Zubair Irshad | 1,569 | 2024-10-26T16:26:41.000Z | false | ||
2406.13457 | 2024-06-24 | EvTexture: Event-driven Texture Enhancement for Video Super-Resolution | [
"Dachun Kai",
"Jiayao Lu",
"Yueyi Zhang",
"Xiaoyan Sun"
] | https://github.com/dachunkai/evtexture | null | 17 | 2 | 17 | 2024-06-24 | 9 | 12 | 12 | 12 | 0 | 12 | true | 2024-W26 | 2024-06 | false | 9 | 27 | 44 | 103 | 168 | 346 | Event-based vision has drawn increasing attention due to its unique
characteristics, such as high temporal resolution and high dynamic range. It
has been used in video super-resolution (VSR) recently to enhance the flow
estimation and temporal alignment. Rather than for motion learning, we propose
in this paper the fir... | [
{
"name": "Dachun Kai",
"user": "BoyDachun",
"fullname": "Dachun Kai",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/noauth/MSTZ1H1JVaANlz2OGt3A3.jpeg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Jiayao Lu",
"user": null,
"fullname": nul... | null | null | null | BoyDachun | Dachun Kai | 1,208 | 2024-06-19T11:27:44.000Z | true | ||
2504.07959 | 2025-04-18 | CCMNet: Leveraging Calibrated Color Correction Matrices for Cross-Camera Color Constancy | [
"Dongyoung Kim",
"Mahmoud Afifi",
"Dongyun Kim",
"Michael S. Brown",
"Seon Joo Kim"
] | https://github.com/DY112/CCMNet | https://www.dykim.me/projects/ccmnet | 9 | 2 | 11 | 2025-04-18 | 7 | 8 | 11 | 11 | 2 | 11 | true | 2025-W16 | 2025-04 | false | 16 | 23 | 63 | 118 | 262 | 456 | Computational color constancy, or white balancing, is a key module in a
camera's image signal processor (ISP) that corrects color casts from scene
lighting. Because this operation occurs in the camera-specific raw color space,
white balance algorithms must adapt to different cameras. This paper introduces
a learning-ba... | [
{
"name": "Dongyoung Kim",
"user": "dongyong2",
"fullname": "Dongyoung Kim",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/645dcc0da19f3e64bbf36492/SPGOweEnV5syFFpf40niQ.png",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Mahmoud Afifi",
"user"... | null | null | null | dongyong2 | Dongyoung Kim | 28 | 2025-04-10T17:59:31.000Z | true | ||
2605.03395 | 2026-05-07 | APEX: Large-scale Multi-task Aesthetic-Informed Popularity Prediction for AI-Generated Music | [
"Jaavid Aktar Husain",
"Dorien Herremans"
] | https://github.com/AMAAI-Lab/apex | null | 6 | 2 | 7 | 2026-05-11 | null | null | null | 5 | 1 | 5 | true | 2026-W19 | 2026-05 | false | 16 | 25 | 87 | 132 | 641 | 939 | Music popularity prediction has attracted growing research interest, with relevance to artists, platforms, and recommendation systems. However, the explosive rise of AI-generated music platforms has created an entirely new and largely unexplored landscape, where a surge of songs is produced and consumed daily without t... | [
{
"name": "Jaavid Aktar Husain",
"user": "Jaavid25",
"fullname": "Jaavid Aktar Husain J",
"avatar": "/avatars/e3fa42f2eb7b83fa103a6722bae6aa90.svg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Dorien Herremans",
"user": "dorienh",
"fullname": "Dorien Herremans... | amaai-lab | AMAAI Lab | dorienh | Dorien Herremans | 10 | 2026-05-05T00:00:00.000Z | true | |||
2602.08519 | 2026-02-11 | Bridging Academia and Industry: A Comprehensive Benchmark for Attributed Graph Clustering | [
"Yunhui Liu",
"Pengyu Qiu",
"Yu Xing",
"Yongchao Liu",
"Peng Du",
"Chuntao Hong",
"Jiajun Zheng",
"Tao Zheng",
"Tieke He"
] | https://github.com/Cloudy1225/PyAGC | https://pyagc.readthedocs.io | 1 | 2 | 1 | 2026-02-11 | 1 | 1 | 1 | 1 | 0 | 1 | true | 2026-W07 | 2026-02 | false | 49 | 57 | 218 | 247 | 675 | 785 | Attributed Graph Clustering (AGC) is a fundamental unsupervised task that integrates structural topology and node attributes to uncover latent patterns in graph-structured data. Despite its significance in industrial applications such as fraud detection and user segmentation, a significant chasm persists between academ... | [
{
"name": "Yunhui Liu",
"user": "Cloudy1225",
"fullname": "Yunhui Liu",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/1673076377130-noauth.jpeg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Pengyu Qiu",
"user": null,
"fullname": null,
... | antgroup | Ant Group | Cloudy1225 | Yunhui Liu | 32 | 2026-02-09T11:07:24.000Z | true | |||
2608.17597 | 2026-08-19 | HarnessRisk: A Lifecycle-Oriented Benchmark for Agent Harness Safety | [
"Yajing Bai",
"Jinhao Duan",
"Jie Peng",
"Xianfeng Wu",
"Sijia Liu",
"Song Wang",
"Tianlong Chen"
] | https://github.com/Baiyajing/HarnessRisk | https://baiyajing.github.io/harness-risk/ | 10 | 2 | 10 | 2026-08-19 | 7 | 8 | 9 | 10 | 0 | 10 | true | 2026-W34 | 2026-08 | false | 19 | 33 | 89 | 153 | 397 | 647 | Large language models are increasingly deployed through agent harnesses that manage tools, extensions, persistent state, permissions, and external actions. Existing safety benchmarks mainly target individual attack mechanisms or a limited subset of operational settings, making it difficult to compare how safety failure... | [
{
"name": "Yajing Bai",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Jinhao Duan",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Jie Peng",
"user": null,
... | null | null | null | Beckham808 | Xianfeng Wu | 22 | 2026-08-18T00:00:00.000Z | false | ||
2507.00339 | 2025-07-02 | Training for X-Ray Vision: Amodal Segmentation, Amodal Content Completion, and View-Invariant Object Representation from Multi-Camera Video | [
"Alexander Moore",
"Amar Saini",
"Kylie Cancilla",
"Doug Poland",
"Carmen Carrano"
] | null | https://huggingface.co/datasets/Amar-S/MOVi-MC-AC | 10 | 1 | 12 | 2025-07-02 | 8 | 9 | 9 | 10 | 2 | 10 | true | 2025-W27 | 2025-07 | false | 9 | 18 | 52 | 91 | 237 | 383 | Amodal segmentation and amodal content completion require using object priors
to estimate occluded masks and features of objects in complex scenes. Until
now, no data has provided an additional dimension for object context: the
possibility of multiple cameras sharing a view of a scene. We introduce
MOVi-MC-AC: Multiple... | [
{
"name": "Alexander Moore",
"user": "tensor-rotator",
"fullname": "Alex Moore",
"avatar": "/avatars/aa25bef1dd651074a93e72be3d1a95c2.svg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Amar Saini",
"user": "Amar-S",
"fullname": "Amar Saini",
"avatar": "http... | null | null | null | Amar-S | Amar Saini | null | 2025-07-01T00:36:56.000Z | true | ||
2509.05209 | 2025-09-11 | Hunyuan-MT Technical Report | [
"Mao Zheng",
"Zheng Li",
"Bingxin Qu",
"Mingyang Song",
"Yang Du",
"Mingrui Sun",
"Di Wang"
] | https://github.com/Tencent-Hunyuan/Hunyuan-MT | https://github.com/Tencent-Hunyuan/Hunyuan-MT | 15 | 3 | 15 | 2025-09-11 | 9 | 10 | 13 | 13 | 0 | 13 | true | 2025-W37 | 2025-09 | false | 8 | 12 | 45 | 92 | 233 | 536 | In this report, we introduce Hunyuan-MT-7B, our first open-source
multilingual translation model, which supports bidirectional translation across
33 major languages and places a special emphasis on translation between
Mandarin and several ethnic minority languages as well as dialects.
Furthermore, to serve and address ... | [
{
"name": "Mao Zheng",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Zheng Li",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Bingxin Qu",
"user": null,
... | null | null | null | Nickyang | Mingyang Song | 724 | 2025-09-05T16:11:05.000Z | false | ||
2312.02135 | 2023-12-05 | Fast View Synthesis of Casual Videos | [
"Yao-Chih Lee",
"Zhoutong Zhang",
"Kevin Blackburn-Matzen",
"Simon Niklaus",
"Jianming Zhang",
"Jia-Bin Huang",
"Feng Liu"
] | null | null | 10 | 1 | 11 | 2024-03-12 | null | null | null | null | 0 | 10 | true | 2023-W49 | 2023-12 | true | 13 | 23 | 62 | 99 | 176 | 293 | Novel view synthesis from an in-the-wild video is difficult due to challenges
like scene dynamics and lack of parallax. While existing methods have shown
promising results with implicit neural radiance fields, they are slow to train
and render. This paper revisits explicit video representations to synthesize
high-quali... | [
{
"name": "Yao-Chih Lee",
"user": "yclee",
"fullname": "Yao-Chih Lee",
"avatar": "/avatars/8888965137382b6f18d806b3e1333ff5.svg",
"status": "admin_assigned",
"hidden": false
},
{
"name": "Zhoutong Zhang",
"user": null,
"fullname": null,
"avatar": null,
"status": null,... | null | null | null | akhaliq | AK | null | 2023-12-04T18:55:48.000Z | false | ||
2605.16819 | 2026-05-19 | AgentKernelArena: Generalization-Aware Benchmarking of GPU Kernel Optimization Agents | [
"Sharareh Younesian",
"Wenwen Ouyang",
"Sina Rafati",
"Mehdi Rezagholizadeh",
"Sharon Zhou",
"Ji Liu",
"Yue Liu",
"Yuchen Yang",
"Hao Li",
"Ziqiong Liu",
"Dong Li",
"Vikram Appia",
"Zhenyu Gu",
"Emad Barsoum"
] | https://github.com/AMD-AGI/AgentKernelArena | null | 2 | 0 | 3 | 2026-05-19 | 1 | 1 | 3 | 3 | 1 | 3 | true | 2026-W21 | 2026-05 | false | 41 | 49 | 207 | 238 | 771 | 939 | GPU kernel optimization is increasingly critical for efficient deep learning systems, but writing high-performance kernels still requires substantial low-level expertise. Recent AI coding agents can iteratively read code, invoke compilers and profilers, and refine implementations, yet existing kernel benchmarks evaluat... | [
{
"name": "Sharareh Younesian",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Wenwen Ouyang",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Sina Rafati",
"u... | null | null | null | taesiri | taesiri | 119 | 2026-05-16T00:00:00.000Z | false | ||
2404.06209 | 2024-04-10 | Elephants Never Forget: Memorization and Learning of Tabular Data in Large Language Models | [
"Sebastian Bordt",
"Harsha Nori",
"Vanessa Rodrigues",
"Besmira Nushi",
"Rich Caruana"
] | https://github.com/interpretml/llm-tabular-memorization-checker | null | 5 | 0 | 5 | 2024-04-10 | 4 | 4 | 4 | 4 | 0 | 4 | true | 2024-W15 | 2024-04 | false | 13 | 13 | 59 | 59 | 198 | 199 | While many have shown how Large Language Models (LLMs) can be applied to a
diverse set of tasks, the critical issues of data contamination and
memorization are often glossed over. In this work, we address this concern for
tabular data. Specifically, we introduce a variety of different techniques to
assess whether a lan... | [
{
"name": "Sebastian Bordt",
"user": "sbordt",
"fullname": "Sebastian Bordt",
"avatar": "/avatars/1efd68debe4249532feb7b8ced1b6a01.svg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Harsha Nori",
"user": null,
"fullname": null,
"avatar": null,
"status":... | null | null | null | akhaliq | AK | 40 | 2024-04-09T10:58:21.000Z | false | ||
2504.17821 | 2025-04-28 | VideoVista-CulturalLingo: 360^circ Horizons-Bridging Cultures, Languages, and Domains in Video Comprehension | [
"Xinyu Chen",
"Yunxin Li",
"Haoyuan Shi",
"Baotian Hu",
"Wenhan Luo",
"Yaowei Wang",
"Min Zhang"
] | https://github.com/HITsz-TMG/VideoVista | https://videovista-culturallingo.github.io/ | 17 | 2 | 24 | 2025-04-28 | 19 | 21 | 21 | 21 | 7 | 21 | true | 2025-W18 | 2025-04 | false | 4 | 12 | 21 | 72 | 148 | 456 | Assessing the video comprehension capabilities of multimodal AI systems can
effectively measure their understanding and reasoning abilities. Most video
evaluation benchmarks are limited to a single language, typically English, and
predominantly feature videos rooted in Western cultural contexts. In this
paper, we prese... | [
{
"name": "Xinyu Chen",
"user": "Ghaser",
"fullname": "Xinyu Chen",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/64d9da538767727dff1e8f19/i16e6wETkGwCFmPoJMh8Q.jpeg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Yunxin Li",
"user": "YunxinLi"... | null | null | null | YunxinLi | Yunxin Li | /avatars/bd03085995b1c34e0ac8a845cf2c4e83.svg | 15 | 2025-04-23T13:47:30.000Z | true | |
2412.06673 | 2024-12-11 | ILLUME: Illuminating Your LLMs to See, Draw, and Self-Enhance | [
"Chunwei Wang",
"Guansong Lu",
"Junwei Yang",
"Runhui Huang",
"Jianhua Han",
"Lu Hou",
"Wei Zhang",
"Hang Xu"
] | null | null | 11 | 2 | 11 | 2024-12-11 | 8 | 10 | 11 | 11 | 0 | 11 | true | 2024-W50 | 2024-12 | false | 16 | 25 | 55 | 102 | 222 | 392 | In this paper, we introduce ILLUME, a unified multimodal large language model
(MLLM) that seamlessly integrates multimodal understanding and generation
capabilities within a single large language model through a unified next-token
prediction formulation. To address the large dataset size typically required
for image-te... | [
{
"name": "Chunwei Wang",
"user": "chunwei0224",
"fullname": "chunwei",
"avatar": "/avatars/936850d0a3f0e4caf55fdaf2937c24ab.svg",
"status": "admin_assigned",
"hidden": false
},
{
"name": "Guansong Lu",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
... | null | null | null | chunwei0224 | chunwei | /avatars/936850d0a3f0e4caf55fdaf2937c24ab.svg | null | 2024-12-09T17:11:50.000Z | true | |
2504.09566 | 2025-04-17 | Syzygy of Thoughts: Improving LLM CoT with the Minimal Free Resolution | [
"Chenghao Li",
"Chaoning Zhang",
"Yi Lu",
"Jiaquan Zhang",
"Qigan Sun",
"Xudong Wang",
"Jiwei Wei",
"Guoqing Wang",
"Yang Yang",
"Heng Tao Shen"
] | https://github.com/dlmaria/syzygy-of-thoughts | null | 11 | 2 | 11 | 2025-04-17 | 2 | 7 | 8 | 10 | 0 | 10 | true | 2025-W16 | 2025-04 | false | 11 | 16 | 70 | 118 | 284 | 456 | Chain-of-Thought (CoT) prompting enhances the reasoning of large language
models (LLMs) by decomposing problems into sequential steps, mimicking human
logic and reducing errors. However, complex tasks with vast solution spaces and
vague constraints often exceed the capacity of a single reasoning chain.
Inspired by Mini... | [
{
"name": "Chenghao Li",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Chaoning Zhang",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Yi Lu",
"user": null,
... | null | null | null | CatWorldLee | Chenghao Li | 133 | 2025-04-13T13:35:41.000Z | false | ||
2605.27760 | 2026-05-28 | SkillGrad: Optimizing Agent Skills Like Gradient Descent | [
"Hanyu Wang",
"Yifan Lan",
"Bochuan Cao",
"Lu Lin",
"Jinghui Chen"
] | https://github.com/wwwhy725/SkillGrad | null | 18 | 2 | 28 | 2026-05-28 | 18 | 23 | 24 | 27 | 10 | 27 | true | 2026-W22 | 2026-05 | false | 14 | 60 | 58 | 240 | 209 | 939 | Agent skills provide a lightweight way to adapt LLM agents to specialized domains by storing reusable procedural knowledge in structured files. However, whether downloaded from third parties or self-generated, these skills are often unreliable, incomplete, or outdated. Existing skill-evolution methods often address the... | [
{
"name": "Hanyu Wang",
"user": "hywww24",
"fullname": "Hanyu Wang",
"avatar": "/avatars/1b95aa71b9aeaa2a0d1dac59535ddd1d.svg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Yifan Lan",
"user": "yflantmy",
"fullname": "Yifan Lan",
"avatar": "https://cdn-avat... | null | null | null | yflantmy | Yifan Lan | 28 | 2026-05-26T00:00:00.000Z | true | ||
2502.03512 | 2025-02-10 | YINYANG-ALIGN: Benchmarking Contradictory Objectives and Proposing Multi-Objective Optimization based DPO for Text-to-Image Alignment | [
"Amitava Das",
"Yaswanth Narsupalli",
"Gurpreet Singh",
"Vinija Jain",
"Vasu Sharma",
"Suranjana Trivedy",
"Aman Chadha",
"Amit Sheth"
] | https://github.com/rom1504/clip-retrieval.Accessed | null | 5 | 2 | 5 | 2025-02-10 | 4 | 5 | 5 | 5 | 0 | 5 | true | 2025-W07 | 2025-02 | false | 21 | 27 | 102 | 122 | 372 | 502 | Precise alignment in Text-to-Image (T2I) systems is crucial to ensure that
generated visuals not only accurately encapsulate user intents but also conform
to stringent ethical and aesthetic benchmarks. Incidents like the Google Gemini
fiasco, where misaligned outputs triggered significant public backlash,
underscore th... | [
{
"name": "Amitava Das",
"user": null,
"fullname": null,
"avatar": null,
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},
{
"name": "Yaswanth Narsupalli",
"user": null,
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},
{
"name": "Gurpreet Singh",
... | null | null | null | amanchadha | Aman Chadha | null | 2025-02-05T18:46:20.000Z | true | ||
2603.03205 | 2026-03-04 | Learning When to Act or Refuse: Guarding Agentic Reasoning Models for Safe Multi-Step Tool Use | [
"Aradhye Agarwal",
"Gurdit Siyan",
"Yash Pandya",
"Joykirat Singh",
"Akshay Nambi",
"Ahmed Awadallah"
] | null | https://aradhye2002.github.io/mosaic-agent-safety/ | 13 | 3 | 13 | 2026-03-04 | 5 | 9 | 11 | 11 | 0 | 11 | true | 2026-W10 | 2026-03 | false | 13 | 43 | 62 | 151 | 324 | 745 | Agentic language models operate in a fundamentally different safety regime than chat models: they must plan, call tools, and execute long-horizon actions where a single misstep, such as accessing files or entering credentials, can cause irreversible harm. Existing alignment methods, largely optimized for static generat... | [
{
"name": "Aradhye Agarwal",
"user": "aradhye",
"fullname": "Aradhye Agarwal",
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"status": "claimed_verified",
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},
{
"name": "Gurdit Siyan",
"user": null,
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"status... | MicrosoftResearch | Microsoft Research | akshaynambi | Akshay Nambi | /avatars/ee7d25d865b34be5902872d060ad9153.svg | null | 2026-03-03T17:59:35.000Z | false | ||
2407.01489 | 2024-07-03 | Agentless: Demystifying LLM-based Software Engineering Agents | [
"Chunqiu Steven Xia",
"Yinlin Deng",
"Soren Dunn",
"Lingming Zhang"
] | https://github.com/OpenAutoCoder/Agentless | null | 63 | 7 | 65 | 2024-07-03 | 20 | 33 | 35 | 37 | 3 | 37 | true | 2024-W27 | 2024-07 | false | 3 | 12 | 10 | 62 | 37 | 345 | Recent advancements in large language models (LLMs) have significantly
advanced the automation of software development tasks, including code
synthesis, program repair, and test generation. More recently, researchers and
industry practitioners have developed various autonomous LLM agents to perform
end-to-end software d... | [
{
"name": "Chunqiu Steven Xia",
"user": "nevetsaix",
"fullname": "Chunqiu Steven Xia",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/645ac350c35da9c7afd82379/nRNoSz0QA2yJmqK3C3F95.jpeg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Yinlin Deng",
... | null | null | null | nevetsaix | Chunqiu Steven Xia | 2,119 | 2024-07-01T17:24:45.000Z | true | ||
2505.02686 | 2025-05-12 | Sailing AI by the Stars: A Survey of Learning from Rewards in Post-Training and Test-Time Scaling of Large Language Models | [
"Xiaobao Wu"
] | https://github.com/bobxwu/learning-from-rewards-llm-papers | null | 16 | 2 | 16 | 2025-05-12 | 11 | 12 | 13 | 14 | 0 | 14 | true | 2025-W20 | 2025-05 | false | 4 | 8 | 36 | 91 | 284 | 730 | Recent developments in Large Language Models (LLMs) have shifted from
pre-training scaling to post-training and test-time scaling. Across these
developments, a key unified paradigm has arisen: Learning from Rewards, where
reward signals act as the guiding stars to steer LLM behavior. It has
underpinned a wide range of ... | [
{
"name": "Xiaobao Wu",
"user": "bobxwu",
"fullname": "Xiaobao Wu",
"avatar": "/avatars/81ce4ba78826b54f0e1b53eeaff87ee6.svg",
"status": "admin_assigned",
"hidden": false
}
] | null | null | null | bobxwu | Xiaobao Wu | /avatars/81ce4ba78826b54f0e1b53eeaff87ee6.svg | 74 | 2025-05-05T14:33:49.000Z | true | |
2507.15550 | 2025-07-22 | PhysGym: Benchmarking LLMs in Interactive Physics Discovery with Controlled Priors | [
"Yimeng Chen",
"Piotr Piȩkos",
"Mateusz Ostaszewski",
"Firas Laakom",
"Jürgen Schmidhuber"
] | null | null | 3 | 2 | 6 | 2025-07-22 | 3 | 3 | 3 | 4 | 3 | 4 | true | 2025-W30 | 2025-07 | false | 23 | 27 | 74 | 86 | 316 | 383 | Evaluating the scientific discovery capabilities of large language model
based agents, particularly how they cope with varying environmental complexity
and utilize prior knowledge, requires specialized benchmarks currently lacking
in the landscape. To address this gap, we introduce PhysGym, a novel benchmark
suite and ... | [
{
"name": "Yimeng Chen",
"user": "YimengChen",
"fullname": "Yimeng Chen",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/no-auth/-h4S4OJYJG02PFkYXKPYX.png",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Piotr Piȩkos",
"user": null,
"fullname... | null | null | null | YimengChen | Yimeng Chen | null | 2025-07-21T12:28:10.000Z | true | ||
2403.13187 | 2024-03-21 | Evolutionary Optimization of Model Merging Recipes | [
"Takuya Akiba",
"Makoto Shing",
"Yujin Tang",
"Qi Sun",
"David Ha"
] | https://github.com/sakanaai/evolutionary-model-merge | null | 58 | 4 | 59 | 2024-03-21 | 22 | 26 | 30 | 41 | 1 | 41 | true | 2024-W12 | 2024-03 | false | 3 | 18 | 8 | 67 | 28 | 218 | We present a novel application of evolutionary algorithms to automate the
creation of powerful foundation models. While model merging has emerged as a
promising approach for LLM development due to its cost-effectiveness, it
currently relies on human intuition and domain knowledge, limiting its
potential. Here, we propo... | [
{
"name": "Takuya Akiba",
"user": "iwiwi",
"fullname": "Takuya Akiba",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/6482810dba6c556892f6f257/c7-wiVKenXiRtwnRpnjZN.jpeg",
"status": "admin_assigned",
"hidden": false
},
{
"name": "Makoto Shing",
"user": "mkshi... | null | null | null | akhaliq | AK | 1,440 | 2024-03-19T22:56:53.000Z | false | ||
2307.03381 | 2023-07-10 | Teaching Arithmetic to Small Transformers | [
"Nayoung Lee",
"Kartik Sreenivasan",
"Jason D. Lee",
"Kangwook Lee",
"Dimitris Papailiopoulos"
] | https://github.com/lee-ny/teaching_arithmetic | null | 20 | 0 | 20 | 2024-03-12 | null | null | null | null | 0 | 20 | true | 2023-W28 | 2023-07 | true | 2 | 7 | 15 | 51 | 55 | 184 | Large language models like GPT-4 exhibit emergent capabilities across
general-purpose tasks, such as basic arithmetic, when trained on extensive text
data, even though these tasks are not explicitly encoded by the unsupervised,
next-token prediction objective. This study investigates how small
transformers, trained fro... | [
{
"name": "Nayoung Lee",
"user": "nayoungl95",
"fullname": "Nayoung Lee",
"avatar": "/avatars/e128d7bf886cdc29a56751c3a75dd8d5.svg",
"status": "extracted_confirmed",
"hidden": false
},
{
"name": "Kartik Sreenivasan",
"user": "ksreenivasan",
"fullname": "Kartik Sreenivasan",
... | null | null | null | akhaliq | AK | 87 | 2023-07-07T04:33:31.000Z | false | ||
2307.05300 | 2023-07-12 | Unleashing Cognitive Synergy in Large Language Models: A Task-Solving Agent through Multi-Persona Self-Collaboration | [
"Zhenhailong Wang",
"Shaoguang Mao",
"Wenshan Wu",
"Tao Ge",
"Furu Wei",
"Heng Ji"
] | https://github.com/mikewangwzhl/solo-performance-prompting | null | 20 | 0 | 20 | 2024-03-12 | null | null | null | null | 0 | 20 | true | 2023-W28 | 2023-07 | true | 4 | 11 | 15 | 51 | 55 | 184 | Human intelligence thrives on the concept of cognitive synergy, where
collaboration and information integration among different cognitive processes
yield superior outcomes compared to individual cognitive processes in
isolation. Although Large Language Models (LLMs) have demonstrated promising
performance as general ta... | [
{
"name": "Zhenhailong Wang",
"user": "mikewang",
"fullname": "Zhenhailong Wang",
"avatar": "/avatars/dff2a3dd10d84b4a73fa486402de7219.svg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Shaoguang Mao",
"user": "dawnmsg",
"fullname": "Shaoguang Mao",
"avatar... | null | null | null | akhaliq | AK | 355 | 2023-07-11T14:45:19.000Z | false | ||
2402.10193 | 2024-02-16 | BitDelta: Your Fine-Tune May Only Be Worth One Bit | [
"James Liu",
"Guangxuan Xiao",
"Kai Li",
"Jason D. Lee",
"Song Han",
"Tri Dao",
"Tianle Cai"
] | https://github.com/FasterDecoding/BitDelta | null | 20 | 6 | 23 | 2024-03-12 | null | null | null | null | 2 | 20 | true | 2024-W07 | 2024-02 | true | 8 | 13 | 18 | 62 | 110 | 256 | Large Language Models (LLMs) are typically trained in two phases:
pre-training on large internet-scale datasets, and fine-tuning for downstream
tasks. Given the higher computational demand of pre-training, it's intuitive to
assume that fine-tuning adds less new information to the model, and is thus
more compressible. W... | [
{
"name": "James Liu",
"user": "jamesliu1",
"fullname": "James Liu",
"avatar": "/avatars/5001cd8965ce6a12a20269ad79a3332b.svg",
"status": "extracted_confirmed",
"hidden": false
},
{
"name": "Guangxuan Xiao",
"user": "Guangxuan-Xiao",
"fullname": "Guangxuan Xiao",
"avatar"... | null | null | null | akhaliq | AK | 206 | 2024-02-15T18:50:06.000Z | true | ||
2403.09338 | 2024-03-15 | LocalMamba: Visual State Space Model with Windowed Selective Scan | [
"Tao Huang",
"Xiaohuan Pei",
"Shan You",
"Fei Wang",
"Chen Qian",
"Chang Xu"
] | https://github.com/hunto/localmamba | null | 8 | 1 | 9 | 2024-03-15 | 7 | 7 | 7 | 7 | 0 | 7 | true | 2024-W11 | 2024-03 | false | 12 | 14 | 43 | 47 | 183 | 218 | Recent advancements in state space models, notably Mamba, have demonstrated
significant progress in modeling long sequences for tasks like language
understanding. Yet, their application in vision tasks has not markedly
surpassed the performance of traditional Convolutional Neural Networks (CNNs)
and Vision Transformers... | [
{
"name": "Tao Huang",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Xiaohuan Pei",
"user": "TerryPei",
"fullname": "TerryPei",
"avatar": "/avatars/9b98943bc609ca974abf0abff3e68633.svg",
"status": "claimed_verified",
... | null | null | null | akhaliq | AK | 285 | 2024-03-14T12:32:40.000Z | false | ||
2509.11526 | 2025-09-17 | Multiple Instance Learning Framework with Masked Hard Instance Mining for Gigapixel Histopathology Image Analysis | [
"Wenhao Tang",
"Sheng Huang",
"Heng Fang",
"Fengtao Zhou",
"Bo Liu",
"Qingshan Liu"
] | https://github.com/DearCaat/MHIM-MIL | null | 2 | 2 | 2 | 2025-09-17 | 1 | 1 | 1 | 1 | 0 | 1 | true | 2025-W38 | 2025-09 | false | 18 | 21 | 88 | 101 | 487 | 536 | Digitizing pathological images into gigapixel Whole Slide Images (WSIs) has
opened new avenues for Computational Pathology (CPath). As positive tissue
comprises only a small fraction of gigapixel WSIs, existing Multiple Instance
Learning (MIL) methods typically focus on identifying salient instances via
attention mecha... | [
{
"name": "Wenhao Tang",
"user": "Dearcat",
"fullname": "Wenhao",
"avatar": "/avatars/5016c566d804d1a00fccbba69059e2ef.svg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Sheng Huang",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"... | null | null | null | Dearcat | Wenhao | /avatars/5016c566d804d1a00fccbba69059e2ef.svg | 97 | 2025-09-15T02:31:33.000Z | true | |
2512.11891 | 2025-12-16 | VLSA: Vision-Language-Action Models with Plug-and-Play Safety Constraint Layer | [
"Songqiao Hu",
"Zeyi Liu",
"Shuang Liu",
"Jun Cen",
"Zihan Meng",
"Xiao He"
] | https://github.com/THU-RCSCT/vlsa-aegis | https://vlsa-aegis.github.io/ | 10 | 2 | 10 | 2025-12-17 | null | 8 | 8 | 8 | 0 | 8 | true | 2025-W51 | 2025-12 | false | 18 | 41 | 87 | 170 | 355 | 633 | Vision-Language-Action (VLA) models have demonstrated remarkable capabilities in generalizing across diverse robotic manipulation tasks. However, deploying these models in unstructured environments remains challenging due to the critical need for simultaneous task compliance and safety assurance, particularly in preven... | [
{
"name": "Songqiao Hu",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Zeyi Liu",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Shuang Liu",
"user": null,
... | null | null | null | jcenaa | Jun CEN | 134 | 2025-12-09T16:53:44.000Z | true | ||
2510.22543 | 2025-10-30 | FAPO: Flawed-Aware Policy Optimization for Efficient and Reliable Reasoning | [
"Yuyang Ding",
"Chi Zhang",
"Juntao Li",
"Haibin Lin",
"Xin Liu",
"Min Zhang"
] | null | https://fapo-rl.github.io/ | 14 | 1 | 14 | 2025-10-30 | 3 | 4 | 4 | 6 | 0 | 6 | true | 2025-W44 | 2025-10 | false | 23 | 30 | 102 | 162 | 533 | 945 | Reinforcement learning with verifiable rewards (RLVR) has emerged as a
promising paradigm for enhancing the reasoning capabilities of large language
models (LLMs). In this context, models explore reasoning trajectories and
exploit rollouts with correct answers as positive signals for policy
optimization. However, these... | [
{
"name": "Yuyang Ding",
"user": "dyyyyyyyy",
"fullname": "Ding",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/626cf0f65651e31a7a2b9779/xES0qcewzvfSIy_0Sqd0u.png",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Chi Zhang",
"user": null,
"fu... | null | null | null | dyyyyyyyy | Ding | null | 2025-10-26T05:49:38.000Z | true | ||
2510.03270 | 2025-10-08 | CoDA: Coding LM via Diffusion Adaptation | [
"Haolin Chen",
"Shiyu Wang",
"Can Qin",
"Bo Pang",
"Zuxin Liu",
"Jielin Qiu",
"Jianguo Zhang",
"Yingbo Zhou",
"Zeyuan Chen",
"Ran Xu",
"Shelby Heinecke",
"Silvio Savarese",
"Caiming Xiong",
"Huan Wang",
"Weiran Yao"
] | https://github.com/SalesforceAIResearch/CoDA | https://huggingface.co/Salesforce/CoDA-v0-Instruct | 43 | 2 | 43 | 2025-10-08 | 25 | 32 | 37 | 39 | 0 | 39 | true | 2025-W41 | 2025-10 | false | 6 | 51 | 25 | 224 | 130 | 945 | Diffusion language models promise bidirectional context and infilling
capabilities that autoregressive coders lack, yet practical systems remain
heavyweight. We introduce CoDA, a 1.7B-parameter diffusion coder trained on TPU
with a fully open-source training pipeline. CoDA pairs large-scale diffusion
pre-training with ... | [
{
"name": "Haolin Chen",
"user": "hlnchen",
"fullname": "Haolin Chen",
"avatar": "/avatars/3210f41fd433d798fd7857c943288625.svg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Shiyu Wang",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
... | Salesforce | Salesforce AI Research | weirayao | Weiran Yao | 67 | 2025-09-27T05:41:55.000Z | false | |||
2601.03194 | 2026-01-07 | X-MuTeST: A Multilingual Benchmark for Explainable Hate Speech Detection and A Novel LLM-consulted Explanation Framework | [
"Mohammad Zia Ur Rehman",
"Sai Kartheek Reddy Kasu",
"Shashivardhan Reddy Koppula",
"Sai Rithwik Reddy Chirra",
"Shwetank Shekhar Singh",
"Nagendra Kumar"
] | https://github.com/ziarehman30/X-MuTeST | null | 3 | 2 | 3 | 2026-01-07 | 1 | 1 | 1 | 1 | 0 | 1 | true | 2026-W02 | 2026-01 | false | 22 | 27 | 104 | 120 | 519 | 573 | Hate speech detection on social media faces challenges in both accuracy and explainability, especially for underexplored Indic languages. We propose a novel explainability-guided training framework, X-MuTeST (eXplainable Multilingual haTe Speech deTection), for hate speech detection that combines high-level semantic re... | [
{
"name": "Mohammad Zia Ur Rehman",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Sai Kartheek Reddy Kasu",
"user": "UVSKKR",
"fullname": "Sai Kartheek Reddy",
"avatar": "/avatars/d5fe48de11e46675b05e1e2e1cf3505c.svg",
"... | null | null | null | UVSKKR | Sai Kartheek Reddy | /avatars/d5fe48de11e46675b05e1e2e1cf3505c.svg | 3 | 2026-01-06T17:16:45.000Z | true | |
2605.14269 | 2026-05-15 | PhyMotion: Structured 3D Motion Reward for Physics-Grounded Human Video Generation | [
"Yidong Huang",
"Zun Wang",
"Han Lin",
"Dong-Ki Kim",
"Shayegan Omidshafiei",
"Jaehong Yoon",
"Jaemin Cho",
"Yue Zhang",
"Mohit Bansal"
] | https://github.com/h6kplus/PhyMotion | https://phy-motion.github.io/ | 6 | 3 | 9 | 2026-05-15 | 4 | 4 | 7 | 9 | 3 | 9 | true | 2026-W20 | 2026-05 | false | 28 | 52 | 131 | 305 | 485 | 939 | Generating realistic human motion is a central yet unsolved challenge in video generation. While reinforcement learning (RL)-based post-training has driven recent gains in general video quality, extending it to human motion remains bottlenecked by a reward signal that cannot reliably score motion realism. Existing vide... | [
{
"name": "Yidong Huang",
"user": "6kplus",
"fullname": "Yidong Huang",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/1665623370422-noauth.jpeg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Zun Wang",
"user": null,
"fullname": null,
"... | UNC-ChapelHill | University of North Carolina at Chapel Hill | hanlincs | Han Lin | /avatars/b89798ff623abffb169eacda2ac32fde.svg | 49 | 2026-05-14T00:00:00.000Z | true | ||
2607.23806 | 2026-07-28 | A Frozen 12B Beats Frontier Models on Verified Work: 100% Accuracy, 0 Tokens, Bit-Exact, Forever | [
"Sietse Schelpe"
] | https://github.com/corbenicai/galahad-bench | https://arxiv.org/abs/2607.23806 | 7 | 4 | 8 | 2026-07-28 | 3 | 6 | 7 | 7 | 1 | 7 | true | 2026-W31 | 2026-07 | false | 19 | 31 | 94 | 138 | 448 | 601 | Improving a language model today means retraining it: enormous compute, a new opaque model each cycle, non-deterministic output. We take the opposite path: the model stays frozen, and a persistent memory of verified solutions grows beside it. Once a problem family is solved and has passed an independent verification st... | [
{
"name": "Sietse Schelpe",
"user": "Corbenic",
"fullname": "sietse schelpe",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/67fcc5ca7f552d4eb0162533/sqFNvSpyuvKmzgUaxayfd.jpeg",
"status": "claimed_verified",
"hidden": false
}
] | Corbenci | Corbenic | Corbenic | sietse schelpe | 1 | 2026-07-26T00:00:00.000Z | true | |||
2608.09848 | 2026-08-11 | CEAA: A Cognitive Embodied Agents Architecture for Interactive Computing Systems | [
"Aimilios Hadjiliasi",
"Louis Nisiotis"
] | null | null | 5 | 2 | 7 | 2026-08-11 | 1 | 5 | 6 | 6 | 2 | 6 | true | 2026-W33 | 2026-08 | false | 33 | 38 | 124 | 155 | 492 | 647 | The development of embodied Intelligent Virtual Agents (IVAs) that have cognitive capabilities in real-time interactive virtual environments remains a challenge, even with today's advancements in technology. Existing architectures are often focused on either the implementation of low-level reactive control systems that... | [
{
"name": "Aimilios Hadjiliasi",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Louis Nisiotis",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
}
] | null | null | null | andreasmartin | Andreas Martin | null | 2026-08-10T00:00:00.000Z | false | ||
2506.15681 | 2025-06-19 | GenRecal: Generation after Recalibration from Large to Small Vision-Language Models | [
"Byung-Kwan Lee",
"Ryo Hachiuma",
"Yong Man Ro",
"Yu-Chiang Frank Wang",
"Yueh-Hua Wu"
] | null | https://byungkwanlee.github.io/GenRecal-page/ | 43 | 2 | 43 | 2025-06-19 | 17 | 25 | 32 | 36 | 1 | 36 | true | 2025-W25 | 2025-06 | false | 2 | 19 | 19 | 127 | 82 | 679 | Recent advancements in vision-language models (VLMs) have leveraged large
language models (LLMs) to achieve performance on par with closed-source systems
like GPT-4V. However, deploying these models in real-world scenarios,
particularly on resource-constrained devices, remains challenging due to their
substantial compu... | [
{
"name": "Byung-Kwan Lee",
"user": "BK-Lee",
"fullname": "Byung-Kwan Lee",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/657152eb12f162153b50ec9d/qnldHP35PclV0pDz_05q8.jpeg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Ryo Hachiuma",
"user":... | nvidia | NVIDIA | BK-Lee | Byung-Kwan Lee | null | 2025-06-18T17:59:49.000Z | true | |||
2503.01372 | 2025-03-06 | SwiLTra-Bench: The Swiss Legal Translation Benchmark | [
"Joel Niklaus",
"Jakob Merane",
"Luka Nenadic",
"Sina Ahmadi",
"Yingqiang Gao",
"Cyrill A. H. Chevalley",
"Claude Humbel",
"Christophe Gösken",
"Lorenzo Tanzi",
"Thomas Lüthi",
"Stefan Palombo",
"Spencer Poff",
"Boling Yang",
"Nan Wu",
"Matthew Guillod",
"Robin Mamié",
"Daniel Brunne... | https://github.com/JoelNiklaus/SwissLegalTranslations | https://huggingface.co/collections/joelniklaus/swiltra-bench-67c569a2ada47e4549733deb | 4 | 2 | 4 | 2025-03-06 | 2 | 2 | 2 | 3 | 0 | 3 | true | 2025-W10 | 2025-03 | false | 17 | 21 | 100 | 114 | 513 | 611 | In Switzerland legal translation is uniquely important due to the country's
four official languages and requirements for multilingual legal documentation.
However, this process traditionally relies on professionals who must be both
legal experts and skilled translators -- creating bottlenecks and impacting
effective ac... | [
{
"name": "Joel Niklaus",
"user": "joelniklaus",
"fullname": "Joel Niklaus",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/1656078368144-5fae5f68b8423e1d80b8a988.jpeg",
"status": "admin_assigned",
"hidden": false
},
{
"name": "Jakob Merane",
"user": null,
... | null | null | null | vansin | vansin | 7 | 2025-03-03T10:10:30.000Z | false | ||
2604.16642 | 2026-04-21 | Geometric coherence of single-cell CRISPR perturbations reveals regulatory architecture and predicts cellular stress | [
"Prashant C. Raju"
] | https://github.com/prashantcraju/geometric-stability-crispr | null | 5 | 2 | 6 | 2026-04-21 | 1 | 1 | 2 | 3 | 1 | 3 | true | 2026-W17 | 2026-04 | false | 31 | 49 | 116 | 166 | 584 | 707 | Single-cell CRISPR screens summarize each perturbation by how far cells move from their unperturbed state, averaging over cell-to-cell variation. Whether the cells moved together is not captured: two perturbations with identical effect magnitude can differ qualitatively, one driving cells along a shared trajectory, the... | [
{
"name": "Prashant C. Raju",
"user": "pcr2120",
"fullname": "Prashant Raju",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/68acd2cd13c9b6d63b82d13d/jJif6PJB3B2sa5b7BVbKR.png",
"status": "claimed_verified",
"hidden": false
}
] | null | null | null | pcr2120 | Prashant Raju | 3 | 2026-08-27T00:00:00.000Z | true | ||
2509.21875 | 2025-09-30 | LUMINA: Detecting Hallucinations in RAG System with Context-Knowledge Signals | [
"Min-Hsuan Yeh",
"Yixuan Li",
"Tanwi Mallick"
] | null | null | 10 | 2 | 10 | 2025-09-30 | 7 | 9 | 9 | 9 | 0 | 9 | true | 2025-W40 | 2025-09 | false | 40 | 82 | 132 | 275 | 286 | 536 | Retrieval-Augmented Generation (RAG) aims to mitigate hallucinations in large
language models (LLMs) by grounding responses in retrieved documents. Yet,
RAG-based LLMs still hallucinate even when provided with correct and sufficient
context. A growing line of work suggests that this stems from an imbalance
between how ... | [
{
"name": "Min-Hsuan Yeh",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Yixuan Li",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Tanwi Mallick",
"user": n... | null | null | null | samuelyeh | Min-Hsuan Yeh | null | 2025-09-26T04:57:46.000Z | false | ||
2309.00071 | 2023-09-04 | YaRN: Efficient Context Window Extension of Large Language Models | [
"Bowen Peng",
"Jeffrey Quesnelle",
"Honglu Fan",
"Enrico Shippole"
] | https://github.com/jquesnelle/yarn | null | 88 | 4 | 88 | 2024-03-12 | null | null | null | null | 0 | 88 | true | 2023-W36 | 2023-09 | true | 1 | 7 | 1 | 42 | 4 | 185 | null | null | null | null | null | null | null | null | null | null | null | null |
2605.07654 | 2026-05-13 | Reliable Chain-of-Thought via Prefix Consistency | [
"Naoto Iwase",
"Yuki Ichihara",
"Mohammad Atif Quamar",
"Junpei Komiyama"
] | https://github.com/naoto-iwase/prefix-consistency | https://naoto-iwase.github.io/prefix-consistency-page | 1 | 3 | 1 | 2026-05-13 | 1 | 1 | 1 | 1 | 0 | 1 | true | 2026-W20 | 2026-05 | false | 56 | 71 | 259 | 305 | 870 | 939 | Large Language Models often improve accuracy on reasoning tasks by sampling multiple Chain-of-Thought (CoT) traces and aggregating them with majority voting (MV), a test-time technique called self-consistency. When we truncate a CoT partway through and regenerate the remainder, we observe that traces with correct answe... | [
{
"name": "Naoto Iwase",
"user": "niwase",
"fullname": "Naoto Iwase",
"avatar": "/avatars/24b31a44cb7b51d4b161f27230a95ed9.svg",
"status": "claimed_verified",
"hidden": true
},
{
"name": "Yuki Ichihara",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
... | MBZUAI | Mohamed Bin Zayed University of Artificial Intelligence | niwase | Naoto Iwase | /avatars/24b31a44cb7b51d4b161f27230a95ed9.svg | 2 | 2026-05-08T00:00:00.000Z | true | ||
2502.13965 | 2025-02-20 | Autellix: An Efficient Serving Engine for LLM Agents as General Programs | [
"Michael Luo",
"Xiaoxiang Shi",
"Colin Cai",
"Tianjun Zhang",
"Justin Wong",
"Yichuan Wang",
"Chi Wang",
"Yanping Huang",
"Zhifeng Chen",
"Joseph E. Gonzalez",
"Ion Stoica"
] | null | null | 19 | 2 | 19 | 2025-02-20 | 14 | 15 | 16 | 18 | 0 | 18 | true | 2025-W08 | 2025-02 | false | 10 | 31 | 44 | 154 | 170 | 502 | Large language model (LLM) applications are evolving beyond simple chatbots
into dynamic, general-purpose agentic programs, which scale LLM calls and
output tokens to help AI agents reason, explore, and solve complex tasks.
However, existing LLM serving systems ignore dependencies between programs and
calls, missing si... | [
{
"name": "Michael Luo",
"user": "michaelzhiluo",
"fullname": "Michael Luo",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/654037be97949fd2304aab7f/2cSME81gcwYa2OTeVlq5Q.jpeg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Xiaoxiang Shi",
"user... | null | null | null | michaelzhiluo | Michael Luo | null | 2025-02-19T18:59:30.000Z | true | ||
2602.01756 | 2026-02-03 | Mind-Brush: Integrating Agentic Cognitive Search and Reasoning into Image Generation | [
"Jun He",
"Junyan Ye",
"Zilong Huang",
"Dongzhi Jiang",
"Chenjue Zhang",
"Leqi Zhu",
"Renrui Zhang",
"Xiang Zhang",
"Weijia Li"
] | https://github.com/PicoTrex/Mind-Brush | null | 23 | 2 | 23 | 2026-02-03 | 21 | 22 | 22 | 22 | 0 | 22 | true | 2026-W06 | 2026-02 | false | 22 | 73 | 72 | 267 | 187 | 785 | While text-to-image generation has achieved unprecedented fidelity, the vast majority of existing models function fundamentally as static text-to-pixel decoders. Consequently, they often fail to grasp implicit user intentions. Although emerging unified understanding-generation models have improved intent comprehension,... | [
{
"name": "Jun He",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Junyan Ye",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Zilong Huang",
"user": "SereinH"... | null | null | null | SereinH | Zilong Huang | 98 | 2026-02-02T07:42:13.000Z | true | ||
2609.35457 | 2026-09-29 | How Far Are We from Removing the Visual Encoder? Scaling Laws for Encoder-Free Multimodal Pretraining | [
"Lin Chen",
"Bolin Ni",
"Qi Yang",
"Lan Jiang",
"Kun Ding",
"Xiaoran Fan",
"Hower Yang",
"Ying Wang",
"Shiming Xiang"
] | null | null | 67 | 2 | 67 | 2026-09-29 | 54 | 59 | 65 | 65 | 0 | 65 | true | 2026-W40 | 2026-09 | false | 11 | 109 | 63 | 404 | 122 | 786 | Most modern multimodal large language models (MLLMs) build on a pretrained visual encoder that provides a strong visual prior. Encoder-free MLLMs instead learn visual representations directly from raw pixels, offering a simple and unified architecture, but their scaling behavior has not been systematically characterize... | [
{
"name": "Lin Chen",
"user": "lchen1019",
"fullname": "Lin Chen",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/6493f25883f6d9c7085f8c3f/F37IzIJ74Y1yhSLa5kFhb.jpeg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Bolin Ni",
"user": null,
"f... | Tencent-Hunyuan | Tencent Hunyuan | YannQi | YannQi | null | 2026-09-28T00:00:00.000Z | true | |||
2609.38445 | 2026-10-01 | AIM: Agentic Idea Management for Automated Research | [
"Hyeong Kyu Choi",
"Bhavana Dalvi Mishra",
"Jiefeng Chen",
"Mihir Parmar",
"Rui Meng",
"Chun-Liang Li",
"Xiangru Tang",
"Sharon Li",
"Jinsung Yoon",
"Tomas Pfister"
] | null | https://imhgchoi.github.io/agentic-idea-manager/ | 52 | 3 | 52 | 2026-10-01 | 40 | 49 | 50 | 51 | 0 | 51 | true | 2026-W40 | 2026-10 | false | 17 | 86 | 80 | 404 | 90 | 532 | Frontier LLMs are increasingly used to automate scientific research through iterative search. We distinguish idea-driven search from solution-driven search and identify three core challenges: organizing evolving research ideas, selecting promising directions, and maintaining alignment between ideas and their implementa... | [
{
"name": "Hyeong Kyu Choi",
"user": "imhgchoi",
"fullname": "Hyeong Kyu (Froilan) Choi",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/64fd0382b8d50cebd669227e/7tMyg1hOoTFXodZCDe_Ol.jpeg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Bhavana Dalv... | google | Google | imhgchoi | Hyeong Kyu (Froilan) Choi | null | 2026-09-29T00:00:00.000Z | true | |||
2407.07080 | 2024-07-10 | Adapting LLMs to Hebrew: Unveiling DictaLM 2.0 with Enhanced Vocabulary and Instruction Capabilities | [
"Shaltiel Shmidman",
"Avi Shmidman",
"Amir DN Cohen",
"Moshe Koppel"
] | null | null | 22 | 1 | 22 | 2024-07-10 | 13 | 14 | 17 | 19 | 0 | 19 | true | 2024-W28 | 2024-07 | false | 5 | 16 | 22 | 83 | 110 | 345 | Training large language models (LLMs) in low-resource languages such as
Hebrew poses unique challenges. In this paper, we introduce DictaLM2.0 and
DictaLM2.0-Instruct, two LLMs derived from the Mistral model, trained on a
substantial corpus of approximately 200 billion tokens in both Hebrew and
English. Adapting a pre-... | [
{
"name": "Shaltiel Shmidman",
"user": "Shaltiel",
"fullname": "Shaltiel Shmidman",
"avatar": "/avatars/668dfce780e1681234f9116822592119.svg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Avi Shmidman",
"user": "avishmidman",
"fullname": "Avi Shmidman",
"av... | null | null | null | Shaltiel | Shaltiel Shmidman | /avatars/668dfce780e1681234f9116822592119.svg | null | 2024-07-09T17:51:37.000Z | true | |
2510.06607 | 2025-10-09 | Code Agent can be an End-to-end System Hacker: Benchmarking Real-world Threats of Computer-use Agent | [
"Weidi Luo",
"Qiming Zhang",
"Tianyu Lu",
"Xiaogeng Liu",
"Bin Hu",
"Hung-Chun Chiu",
"Siyuan Ma",
"Yizhe Zhang",
"Xusheng Xiao",
"Yinzhi Cao",
"Zhen Xiang",
"Chaowei Xiao"
] | https://github.com/google-gemini/gemini-cli | https://eddyluo.com/AdvCUA/ | 2 | 2 | 4 | 2025-10-09 | 2 | 3 | 3 | 3 | 2 | 3 | true | 2025-W41 | 2025-10 | false | 30 | 43 | 148 | 224 | 685 | 945 | Computer-use agent (CUA) frameworks, powered by large language models (LLMs)
or multimodal LLMs (MLLMs), are rapidly maturing as assistants that can
perceive context, reason, and act directly within software environments. Among
their most critical applications is operating system (OS) control. As CUAs in
the OS domain ... | [
{
"name": "Weidi Luo",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Qiming Zhang",
"user": "TerryZhang08",
"fullname": "Qiming Zhang",
"avatar": "/avatars/1a7b776c327cda5190170c32a9b23694.svg",
"status": "claimed_verifi... | MomoUchi | MomoUchi | https://www.gravatar.com/avatar/232f2099db570d05da8098e4c54bdf37?d=retro&size=100 | EddyLuo | WeidiLuo | null | 2025-10-08T03:35:23.000Z | false | ||
2601.04544 | 2026-01-12 | TCAndon-Router: Adaptive Reasoning Router for Multi-Agent Collaboration | [
"Jiuzhou Zhao",
"Chunrong Chen",
"Chenqi Qiao",
"Lebin Zheng",
"Minqi Han",
"Yanchi Liu Yongzhou Xu Xiaochuan Xu Min Zhang"
] | https://github.com/Tencent/TCAndon-Router | null | 7 | 4 | 7 | 2026-01-12 | 2 | 4 | 4 | 4 | 0 | 4 | true | 2026-W03 | 2026-01 | false | 22 | 31 | 116 | 162 | 420 | 573 | Multi-Agent Systems(MAS) have become a powerful paradigm for building high performance intelligent applications. Within these systems, the router responsible for determining which expert agents should handle a given query plays a crucial role in overall performance. Existing routing strategies generally fall into two c... | [
{
"name": "Jiuzhou Zhao",
"user": "joska",
"fullname": "joskazhao",
"avatar": "/avatars/8c329eab4e2216c2c51565b48376cb03.svg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Chunrong Chen",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
... | tencent | Tencent | nielsr | Niels Rogge | 18 | 2026-01-08T03:17:33.000Z | false | |||
2506.17930 | 2025-07-01 | Evolving Prompts In-Context: An Open-ended, Self-replicating Perspective | [
"Jianyu Wang",
"Zhiqiang Hu",
"Lidong Bing"
] | https://github.com/jianyu-cs/promptquine | null | 19 | 2 | 19 | 2025-07-01 | 16 | 16 | 17 | 19 | 0 | 19 | true | 2025-W27 | 2025-07 | false | 7 | 19 | 32 | 91 | 165 | 383 | We propose a novel prompt design paradigm that challenges conventional wisdom
in large language model (LLM) prompting. While conventional wisdom prioritizes
well-crafted instructions and demonstrations for in-context learning (ICL), we
show that pruning random demonstrations into seemingly incoherent "gibberish"
can re... | [
{
"name": "Jianyu Wang",
"user": "Jianyu",
"fullname": "Jianyu Wang",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/1642110635503-noauth.jpeg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Zhiqiang Hu",
"user": "Zhiqiang007",
"fullname": "... | null | null | null | Jianyu | Jianyu Wang | 16 | 2025-06-22T07:53:07.000Z | true | ||
2510.07841 | 2025-10-14 | Self-Improving LLM Agents at Test-Time | [
"Emre Can Acikgoz",
"Cheng Qian",
"Heng Ji",
"Dilek Hakkani-Tür",
"Gokhan Tur"
] | null | null | 10 | 2 | 10 | 2025-10-14 | 7 | 9 | 9 | 9 | 0 | 9 | true | 2025-W42 | 2025-10 | false | 30 | 57 | 112 | 244 | 445 | 945 | One paradigm of language model (LM) fine-tuning relies on creating large
training datasets, under the assumption that high quantity and diversity will
enable models to generalize to novel tasks after post-training. In practice,
gathering large sets of data is inefficient, and training on them is
prohibitively expensive... | [
{
"name": "Emre Can Acikgoz",
"user": "emrecanacikgoz",
"fullname": "emre can",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/63888d3fd68e37abd599f428/YaNyxG_oM6IgrHTkFZ6Eq.jpeg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Cheng Qian",
"user... | null | null | null | emrecanacikgoz | emre can | null | 2025-10-09T06:37:35.000Z | true | ||
2410.01171 | 2024-10-03 | BordIRlines: A Dataset for Evaluating Cross-lingual Retrieval-Augmented Generation | [
"Bryan Li",
"Samar Haider",
"Fiona Luo",
"Adwait Agashe",
"Chris Callison-Burch"
] | https://github.com/manestay/bordirlines | null | 5 | 4 | 6 | 2024-10-03 | 1 | 4 | 5 | 5 | 0 | 5 | true | 2024-W40 | 2024-10 | false | 14 | 24 | 69 | 88 | 369 | 482 | Large language models excel at creative generation but continue to struggle
with the issues of hallucination and bias. While retrieval-augmented generation
(RAG) provides a framework for grounding LLMs' responses in accurate and
up-to-date information, it still raises the question of bias: which sources
should be selec... | [
{
"name": "Bryan Li",
"user": "manestay",
"fullname": "Bryan Li",
"avatar": "/avatars/3f02c0d1fad478722f180d9559ae215d.svg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Samar Haider",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
... | null | null | null | manestay | Bryan Li | /avatars/3f02c0d1fad478722f180d9559ae215d.svg | 1 | 2024-10-02T01:59:07.000Z | true | |
2509.20360 | 2025-09-25 | EditVerse: Unifying Image and Video Editing and Generation with In-Context Learning | [
"Xuan Ju",
"Tianyu Wang",
"Yuqian Zhou",
"He Zhang",
"Qing Liu",
"Nanxuan Zhao",
"Zhifei Zhang",
"Yijun Li",
"Yuanhao Cai",
"Shaoteng Liu",
"Daniil Pakhomov",
"Zhe Lin",
"Soo Ye Kim",
"Qiang Xu"
] | https://github.com/itseez/opencv | null | 18 | 2 | 18 | 2025-09-25 | 9 | 14 | 16 | 16 | 0 | 16 | true | 2025-W39 | 2025-09 | false | 4 | 14 | 42 | 129 | 203 | 536 | Recent advances in foundation models highlight a clear trend toward
unification and scaling, showing emergent capabilities across diverse domains.
While image generation and editing have rapidly transitioned from task-specific
to unified frameworks, video generation and editing remain fragmented due to
architectural li... | [
{
"name": "Xuan Ju",
"user": "juxuan27",
"fullname": "Xuan Ju",
"avatar": "/avatars/a3a5729e33ae89ce9ba408830db3c835.svg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Tianyu Wang",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hi... | null | null | null | taesiri | taesiri | null | 2025-09-24T17:59:30.000Z | false | ||
2510.09535 | 2025-10-13 | Mitigating Overthinking through Reasoning Shaping | [
"Feifan Song",
"Shaohang Wei",
"Bofei Gao",
"Yejie Wang",
"Wen Luo",
"Wei Li",
"Linli Yao",
"Weimin Xiong",
"Liang Chen",
"Tianyu Liu",
"Houfeng Wang"
] | null | null | 5 | 3 | 5 | 2025-10-13 | 2 | 4 | 4 | 4 | 0 | 4 | true | 2025-W42 | 2025-10 | false | 31 | 46 | 162 | 244 | 625 | 945 | Large reasoning models (LRMs) boosted by Reinforcement Learning from Verifier
Reward (RLVR) have shown great power in problem solving, yet they often cause
overthinking: excessive, meandering reasoning that inflates computational cost.
Prior designs of penalization in RLVR manage to reduce token consumption while
often... | [
{
"name": "Feifan Song",
"user": "songff",
"fullname": "Feifan Song",
"avatar": "/avatars/5049856b5ed1b74533fff902e14b4c7c.svg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Shaohang Wei",
"user": "SylvainWei",
"fullname": "Shaohang Wei",
"avatar": "https:/... | null | null | null | songff | Feifan Song | /avatars/5049856b5ed1b74533fff902e14b4c7c.svg | null | 2025-10-10T16:49:03.000Z | true | |
2510.20187 | 2025-10-24 | Every Question Has Its Own Value: Reinforcement Learning with Explicit Human Values | [
"Dian Yu",
"Yulai Zhao",
"Kishan Panaganti",
"Linfeng Song",
"Haitao Mi",
"Dong Yu"
] | null | null | 19 | 2 | 20 | 2025-10-24 | 13 | 16 | 17 | 18 | 1 | 18 | true | 2025-W43 | 2025-10 | false | 8 | 28 | 57 | 166 | 296 | 945 | We propose Reinforcement Learning with Explicit Human Values (RLEV), a method
that aligns Large Language Model (LLM) optimization directly with quantifiable
human value signals. While Reinforcement Learning with Verifiable Rewards
(RLVR) effectively trains models in objective domains using binary correctness
rewards, i... | [
{
"name": "Dian Yu",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Yulai Zhao",
"user": "sarosavo",
"fullname": "Yulai Zhao",
"avatar": "/avatars/c032c1b942b3cb9450a49db88fce5c70.svg",
"status": "claimed_verified",
"... | tencent | Tencent | yudian | Dian Yu | /avatars/7a4f3ee4a37245f67efd26749d66a706.svg | null | 2025-10-23T04:15:22.000Z | false | ||
2307.03183 | 2023-07-07 | Whisper-AT: Noise-Robust Automatic Speech Recognizers are Also Strong General Audio Event Taggers | [
"Yuan Gong",
"Sameer Khurana",
"Leonid Karlinsky",
"James Glass"
] | https://github.com/YuanGongND/whisper-at | null | 10 | 0 | 10 | 2024-03-12 | null | null | null | null | 0 | 10 | true | 2023-W27 | 2023-07 | true | 6 | 8 | 21 | 44 | 105 | 184 | In this paper, we focus on Whisper, a recent automatic speech recognition
model trained with a massive 680k hour labeled speech corpus recorded in
diverse conditions. We first show an interesting finding that while Whisper is
very robust against real-world background sounds (e.g., music), its audio
representation is ac... | [
{
"name": "Yuan Gong",
"user": "yuangongfdu",
"fullname": "Yuan Gong",
"avatar": "/avatars/24c98c05509fa7b1ac3371ceb1b81f67.svg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Sameer Khurana",
"user": "skhurana",
"fullname": "Sameer Khurana",
"avatar": "/ava... | null | null | null | akhaliq | AK | 426 | 2023-07-06T17:58:28.000Z | false | ||
2606.16519 | 2026-06-16 | BadWorld: Adversarial Attacks on World Models | [
"Linghui Shen",
"Mingyue Cui",
"Xingyi Yang"
] | https://github.com/LinghuiiShen/BadWorld | https://linghuiishen.github.io/BadWorld/ | 16 | 1 | 18 | 2026-06-16 | 14 | 14 | 15 | 18 | 2 | 18 | true | 2026-W25 | 2026-06 | false | 11 | 42 | 54 | 192 | 280 | 946 | Visual world models (VWMs) synthesize interactive, action-conditioned rollouts from a single context image. However, it remains an open question how robust these models are to adversarial perturbations. Standard adversarial attacks fail to assess this vulnerability because attackers lack ground-truth future videos and ... | [
{
"name": "Linghui Shen",
"user": "LinghuiShen",
"fullname": "Shen Linghui",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/no-auth/2liMvKYwnE2xNGmpE_GwW.png",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Mingyue Cui",
"user": "Mingyueee",
... | PolyUHK | The Hong Kong Polytechnic University | adamdad | Xingyi Yang | 19 | 2026-06-15T00:00:00.000Z | true | |||
2510.15564 | 2025-10-20 | Imaginarium: Vision-guided High-Quality 3D Scene Layout Generation | [
"Xiaoming Zhu",
"Xu Huang",
"Qinghongbing Xie",
"Zhi Deng",
"Junsheng Yu",
"Yirui Guan",
"Zhongyuan Liu",
"Lin Zhu",
"Qijun Zhao",
"Ligang Liu",
"Long Zeng"
] | https://github.com/HiHiAllen/Imaginarium | null | 11 | 3 | 11 | 2025-10-20 | 8 | 9 | 9 | 9 | 0 | 9 | true | 2025-W43 | 2025-10 | false | 20 | 28 | 84 | 166 | 445 | 945 | Generating artistic and coherent 3D scene layouts is crucial in digital
content creation. Traditional optimization-based methods are often constrained
by cumbersome manual rules, while deep generative models face challenges in
producing content with richness and diversity. Furthermore, approaches that
utilize large lan... | [
{
"name": "Xiaoming Zhu",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Xu Huang",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Qinghongbing Xie",
"user": ... | null | null | null | taesiri | taesiri | 66 | 2025-10-17T11:48:08.000Z | false | ||
2306.07075 | 2023-06-13 | Large Language Models as Tax Attorneys: A Case Study in Legal Capabilities Emergence | [
"John J. Nay",
"David Karamardian",
"Sarah B. Lawsky",
"Wenting Tao",
"Meghana Bhat",
"Raghav Jain",
"Aaron Travis Lee",
"Jonathan H. Choi",
"Jungo Kasai"
] | null | null | 11 | 5 | 11 | 2024-03-12 | null | null | null | null | 0 | 11 | true | 2023-W24 | 2023-06 | true | 8 | 12 | 27 | 64 | 79 | 257 | Better understanding of Large Language Models' (LLMs) legal analysis
abilities can contribute to improving the efficiency of legal services,
governing artificial intelligence, and leveraging LLMs to identify
inconsistencies in law. This paper explores LLM capabilities in applying tax
law. We choose this area of law bec... | [
{
"name": "John J. Nay",
"user": "johnjnay",
"fullname": "John Nay",
"avatar": "/avatars/4076a12ac9423ab276d06334c7e392db.svg",
"status": "admin_assigned",
"hidden": false
},
{
"name": "David Karamardian",
"user": null,
"fullname": null,
"avatar": null,
"status": null... | null | null | null | akhaliq | AK | null | 2023-06-12T12:40:48.000Z | true |
End of preview. Expand in Data Studio
Paper Pulse data
The day-by-day upvote history of every Hugging Face Daily Papers entry since 2024-03-12, updated every day. It powers Paper Pulse (Space).
Built from the past revisions of hysts-bot-data/daily-papers-stats and the paper list in hysts-bot-data/daily-papers, both by @hysts, plus paper details from the public Daily Papers API. Thanks to hysts for keeping that record and for releasing it under CC0 1.0.
Files
| File | Rows | What it holds |
|---|---|---|
series.parquet |
one per paper per day | id (arXiv id), day, upvotes, comments: the count shown on the paper's page that day (last snapshot of the day, UTC) |
papers.parquet |
one per paper | title, Daily Papers date, authors (with Hugging Face accounts when linked), organization, submitter, GitHub repo and stars, abstract (summary), upvotes on day 0/1/3/7, up_close (7 days after the Daily Papers date), peak, purged, and rank within its day, ISO week and month |
purges.parquet |
one per event | days when the Hub removed votes from many papers at once: papers affected (n_drop), votes removed, and whether it was deep |
hourly.parquet |
one per paper per hour | id, ts (UTC), upvotes for the papers featured in the last 10 days, from the hourly snapshots of daily-papers-stats |
age_stats.json |
how papers usually do by age: the distribution of upvotes at the end of day 0..7 after their Daily Papers date, and what papers with a given count at day k ended their first week with (ratios by count bin) | |
meta.json |
last day, number of papers, purge days |
Notes
- Upvotes can go down. People unvote, and on a few days the Hub removed votes from many papers at once (2025-09-12, 2025-12-23, 2026-09-16, 2026-09-18; the cause was not announced). The series keeps the raw value of each day and never corrects it. A day counts as a purge when at least max(250, 2% of papers) dropped.
- Rankings use
up_close, the upvotes 7 days after the Daily Papers date, so a later purge does not rewrite past rankings. Papers younger than 7 days are ranked by their current count, and so are the papers whose Daily Papers date is before the history starts (March 12, 2024), which are flagged withearly. - The source has two collection gaps (13 and 7 days). Days without a snapshot have no row.
- Only papers that were featured on Daily Papers are included (about 18,500), not every paper on the Hub.
License
The series, rankings and purge records are released under CC BY 4.0. The source datasets by @hysts are CC0 1.0. Paper titles and abstracts (title, summary) belong to their authors and are included only to identify each paper; they are not covered by this dataset's license.
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