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Collections including paper arxiv:2502.01142

Evolving Deeper LLM Thinking

Paper • 2501.09891 • Published Jan 17 • 106
PaSa: An LLM Agent for Comprehensive Academic Paper Search

Paper • 2501.10120 • Published Jan 17 • 44
Multiple Choice Questions: Reasoning Makes Large Language Models (LLMs) More Self-Confident Even When They Are Wrong

Paper • 2501.09775 • Published Jan 16 • 29
ComplexFuncBench: Exploring Multi-Step and Constrained Function Calling under Long-Context Scenario

Paper • 2501.10132 • Published Jan 17 • 19

RPO: Retrieval Preference Optimization for Robust Retrieval-Augmented Generation

Paper • 2501.13726 • Published Jan 23
RAG-Star: Enhancing Deliberative Reasoning with Retrieval Augmented Verification and Refinement

Paper • 2412.12881 • Published Dec 17, 2024 • 2
DeepRAG: Thinking to Retrieval Step by Step for Large Language Models

Paper • 2502.01142 • Published Feb 3 • 24

about 1 month ago

Rethinking Mixture-of-Agents: Is Mixing Different Large Language Models Beneficial?

Paper • 2502.00674 • Published Feb 2 • 13
Demystifying Long Chain-of-Thought Reasoning in LLMs

Paper • 2502.03373 • Published Feb 5 • 56
SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Model

Paper • 2502.02737 • Published Feb 4 • 203
DeepRAG: Thinking to Retrieval Step by Step for Large Language Models

Paper • 2502.01142 • Published Feb 3 • 24

DeepRAG: Thinking to Retrieval Step by Step for Large Language Models

Paper • 2502.01142 • Published Feb 3 • 24

DeepRAG: Thinking to Retrieval Step by Step for Large Language Models

Paper • 2502.01142 • Published Feb 3 • 24

DeepRAG: Thinking to Retrieval Step by Step for Large Language Models

Paper • 2502.01142 • Published Feb 3 • 24

MM-IQ: Benchmarking Human-Like Abstraction and Reasoning in Multimodal Models

Paper • 2502.00698 • Published Feb 2 • 24
DeepRAG: Thinking to Retrieval Step by Step for Large Language Models

Paper • 2502.01142 • Published Feb 3 • 24
ZebraLogic: On the Scaling Limits of LLMs for Logical Reasoning

Paper • 2502.01100 • Published Feb 3 • 17
The Jumping Reasoning Curve? Tracking the Evolution of Reasoning Performance in GPT-[n] and o-[n] Models on Multimodal Puzzles

Paper • 2502.01081 • Published Feb 3 • 14

Retrieval Augmented Generation (RAG)

Chain-of-Retrieval Augmented Generation

Paper • 2501.14342 • Published Jan 24 • 52
DeepRAG: Thinking to Retrieval Step by Step for Large Language Models

Paper • 2502.01142 • Published Feb 3 • 24
SafeRAG: Benchmarking Security in Retrieval-Augmented Generation of Large Language Model

Paper • 2501.18636 • Published Jan 28 • 29

rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking

Paper • 2501.04519 • Published Jan 8 • 263
URSA: Understanding and Verifying Chain-of-thought Reasoning in Multimodal Mathematics

Paper • 2501.04686 • Published Jan 8 • 50
Towards System 2 Reasoning in LLMs: Learning How to Think With Meta Chain-of-Though

Paper • 2501.04682 • Published Jan 8 • 91
Agent Laboratory: Using LLM Agents as Research Assistants

Paper • 2501.04227 • Published Jan 8 • 86

2025 LLM Papers on Hugging Face with Japanese Memos

MotionBench: Benchmarking and Improving Fine-grained Video Motion Understanding for Vision Language Models

Paper • 2501.02955 • Published Jan 6 • 40
2.5 Years in Class: A Multimodal Textbook for Vision-Language Pretraining

Paper • 2501.00958 • Published Jan 1 • 100
MMVU: Measuring Expert-Level Multi-Discipline Video Understanding

Paper • 2501.12380 • Published Jan 21 • 84
VideoWorld: Exploring Knowledge Learning from Unlabeled Videos

Paper • 2501.09781 • Published Jan 16 • 27

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