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Collections including paper arxiv:2403.10131

AI Paper of the Day

A collection of papers that I think are interesting, one added each day

Can Large Language Models Understand Context?

Paper • 2402.00858 • Published Feb 1 • 21
OLMo: Accelerating the Science of Language Models

Paper • 2402.00838 • Published Feb 1 • 75
Self-Rewarding Language Models

Paper • 2401.10020 • Published Jan 18 • 138
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity

Paper • 2401.17072 • Published Jan 30 • 25

Self-Rewarding Language Models

Paper • 2401.10020 • Published Jan 18 • 138
ReFT: Reasoning with Reinforced Fine-Tuning

Paper • 2401.08967 • Published Jan 17 • 27
Tuning Language Models by Proxy

Paper • 2401.08565 • Published Jan 16 • 20
TrustLLM: Trustworthiness in Large Language Models

Paper • 2401.05561 • Published Jan 10 • 63

LLMLingua-2: Data Distillation for Efficient and Faithful Task-Agnostic Prompt Compression

Paper • 2403.12968 • Published Mar 19 • 24
PERL: Parameter Efficient Reinforcement Learning from Human Feedback

Paper • 2403.10704 • Published Mar 15 • 56
Alignment Studio: Aligning Large Language Models to Particular Contextual Regulations

Paper • 2403.09704 • Published Mar 8 • 30
RAFT: Adapting Language Model to Domain Specific RAG

Paper • 2403.10131 • Published Mar 15 • 65

PDFTriage: Question Answering over Long, Structured Documents

Paper • 2309.08872 • Published Sep 16, 2023 • 52
Adapting Large Language Models via Reading Comprehension

Paper • 2309.09530 • Published Sep 18, 2023 • 75
Table-GPT: Table-tuned GPT for Diverse Table Tasks

Paper • 2310.09263 • Published Oct 13, 2023 • 38
Context-Aware Meta-Learning

Paper • 2310.10971 • Published Oct 17, 2023 • 14

Instruction Pre-Training: Language Models are Supervised Multitask Learners

Paper • 2406.14491 • Published Jun 20 • 78
Better & Faster Large Language Models via Multi-token Prediction

Paper • 2404.19737 • Published Apr 30 • 72
RAFT: Adapting Language Model to Domain Specific RAG

Paper • 2403.10131 • Published Mar 15 • 65
The Prompt Report: A Systematic Survey of Prompting Techniques

Paper • 2406.06608 • Published Jun 6 • 48

Plot2Code: A Comprehensive Benchmark for Evaluating Multi-modal Large Language Models in Code Generation from Scientific Plots

Paper • 2405.07990 • Published May 13 • 15
Large Language Models as Planning Domain Generators

Paper • 2405.06650 • Published Apr 2 • 8
AutoCrawler: A Progressive Understanding Web Agent for Web Crawler Generation

Paper • 2404.12753 • Published Apr 19 • 40
OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments

Paper • 2404.07972 • Published Apr 11 • 41

Fine Tuning vs. Retrieval Augmented Generation for Less Popular Knowledge

Paper • 2403.01432 • Published Mar 3 • 2
RAFT: Adapting Language Model to Domain Specific RAG

Paper • 2403.10131 • Published Mar 15 • 65
BLADE: Enhancing Black-box Large Language Models with Small Domain-Specific Models

Paper • 2403.18365 • Published Mar 27 • 2
When to Retrieve: Teaching LLMs to Utilize Information Retrieval Effectively

Paper • 2404.19705 • Published Apr 30

Smarter LLMs Research

RARR: Researching and Revising What Language Models Say, Using Language Models

Paper • 2210.08726 • Published Oct 17, 2022 • 1
Hypothesis Search: Inductive Reasoning with Language Models

Paper • 2309.05660 • Published Sep 11, 2023 • 1
In-context Learning and Induction Heads

Paper • 2209.11895 • Published Sep 24, 2022 • 2
ReAct: Synergizing Reasoning and Acting in Language Models

Paper • 2210.03629 • Published Oct 6, 2022 • 13

Beyond Chain-of-Thought: A Survey of Chain-of-X Paradigms for LLMs

Paper • 2404.15676 • Published Apr 24
How faithful are RAG models? Quantifying the tug-of-war between RAG and LLMs' internal prior

Paper • 2404.10198 • Published Apr 16 • 7
RAFT: Adapting Language Model to Domain Specific RAG

Paper • 2403.10131 • Published Mar 15 • 65
FaaF: Facts as a Function for the evaluation of RAG systems

Paper • 2403.03888 • Published Mar 6

Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks

Paper • 2005.11401 • Published May 22, 2020 • 11
RAG vs Fine-tuning: Pipelines, Tradeoffs, and a Case Study on Agriculture

Paper • 2401.08406 • Published Jan 16 • 37
BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models

Paper • 2104.08663 • Published Apr 17, 2021 • 3
Precise Zero-Shot Dense Retrieval without Relevance Labels

Paper • 2212.10496 • Published Dec 20, 2022 • 2

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