Diffusion Augmented Agents: A Framework for Efficient Exploration and Transfer Learning
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2407.20798
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Published
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25
Reinforcement learning
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Offline Reinforcement Learning for LLM Multi-Step Reasoning
Paper • 2412.16145 • Published • 39 -
REINFORCE++: A Simple and Efficient Approach for Aligning Large Language Models
Paper • 2501.03262 • Published • 100 -
SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software Evolution
Paper • 2502.18449 • Published • 74 -
Learning to Reason under Off-Policy Guidance
Paper • 2504.14945 • Published • 85 -
LLMs are Greedy Agents: Effects of RL Fine-tuning on Decision-Making Abilities
Paper • 2504.16078 • Published • 20 -
OTC: Optimal Tool Calls via Reinforcement Learning
Paper • 2504.14870 • Published • 33 -
Reinforcement Learning for Reasoning in Large Language Models with One Training Example
Paper • 2504.20571 • Published • 94 -
Thinkless: LLM Learns When to Think
Paper • 2505.13379 • Published • 50 -
Visual Agentic Reinforcement Fine-Tuning
Paper • 2505.14246 • Published • 31 -
Reinforcement Learning Finetunes Small Subnetworks in Large Language Models
Paper • 2505.11711 • Published • 10 -
Scaling Reasoning, Losing Control: Evaluating Instruction Following in Large Reasoning Models
Paper • 2505.14810 • Published • 61 -
TinyV: Reducing False Negatives in Verification Improves RL for LLM Reasoning
Paper • 2505.14625 • Published • 13 -
ConvSearch-R1: Enhancing Query Reformulation for Conversational Search with Reasoning via Reinforcement Learning
Paper • 2505.15776 • Published • 10 -
Teaching Large Language Models to Maintain Contextual Faithfulness via Synthetic Tasks and Reinforcement Learning
Paper • 2505.16483 • Published • 10 -
One RL to See Them All: Visual Triple Unified Reinforcement Learning
Paper • 2505.18129 • Published • 59 -
Synthetic Data RL: Task Definition Is All You Need
Paper • 2505.17063 • Published • 10 -
ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models
Paper • 2505.24864 • Published • 120 -
Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning
Paper • 2506.01939 • Published • 148 -
Reinforcement Pre-Training
Paper • 2506.08007 • Published • 181