Visual-RFT: Visual Reinforcement Fine-Tuning
Paper
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2503.01785
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Published
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78
Backlog
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When an LLM is apprehensive about its answers -- and when its uncertainty is justified
Paper • 2503.01688 • Published • 21 -
Predictive Data Selection: The Data That Predicts Is the Data That Teaches
Paper • 2503.00808 • Published • 57 -
Chain of Draft: Thinking Faster by Writing Less
Paper • 2502.18600 • Published • 48 -
Multi-Turn Code Generation Through Single-Step Rewards
Paper • 2502.20380 • Published • 31 -
Self-rewarding correction for mathematical reasoning
Paper • 2502.19613 • Published • 84 -
MPO: Boosting LLM Agents with Meta Plan Optimization
Paper • 2503.02682 • Published • 27 -
rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking
Paper • 2501.04519 • Published • 277 -
SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training
Paper • 2501.17161 • Published • 120 -
Evolving Deeper LLM Thinking
Paper • 2501.09891 • Published • 114 -
AgentTuning: Enabling Generalized Agent Abilities for LLMs
Paper • 2310.12823 • Published • 35 -
Search-o1: Agentic Search-Enhanced Large Reasoning Models
Paper • 2501.05366 • Published • 102 -
The Lessons of Developing Process Reward Models in Mathematical Reasoning
Paper • 2501.07301 • Published • 99 -
REINFORCE++: A Simple and Efficient Approach for Aligning Large Language Models
Paper • 2501.03262 • Published • 99 -
Towards System 2 Reasoning in LLMs: Learning How to Think With Meta Chain-of-Though
Paper • 2501.04682 • Published • 98 -
Agent Laboratory: Using LLM Agents as Research Assistants
Paper • 2501.04227 • Published • 91 -
OS-Genesis: Automating GUI Agent Trajectory Construction via Reverse Task Synthesis
Paper • 2412.19723 • Published • 89 -
GuardReasoner: Towards Reasoning-based LLM Safeguards
Paper • 2501.18492 • Published • 87 -
Towards Best Practices for Open Datasets for LLM Training
Paper • 2501.08365 • Published • 61 -
Qwen2.5 Technical Report
Paper • 2412.15115 • Published • 365 -
RobustFT: Robust Supervised Fine-tuning for Large Language Models under Noisy Response
Paper • 2412.14922 • Published • 89 -
Training Large Language Models to Reason in a Continuous Latent Space
Paper • 2412.06769 • Published • 84 -
OpenCoder: The Open Cookbook for Top-Tier Code Large Language Models
Paper • 2411.04905 • Published • 124 -
Training Language Models to Self-Correct via Reinforcement Learning
Paper • 2409.12917 • Published • 140 -
Survey on Evaluation of LLM-based Agents
Paper • 2503.16416 • Published • 89 -
Large Language Model Agent: A Survey on Methodology, Applications and Challenges
Paper • 2503.21460 • Published • 77 -
A Survey of Efficient Reasoning for Large Reasoning Models: Language, Multimodality, and Beyond
Paper • 2503.21614 • Published • 39