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Towards General-Purpose Model-Free Reinforcement Learning
Paper • 2501.16142 • Published • 30 -
DAPO: An Open-Source LLM Reinforcement Learning System at Scale
Paper • 2503.14476 • Published • 141 -
Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?
Paper • 2504.13837 • Published • 135 -
Learning to Reason under Off-Policy Guidance
Paper • 2504.14945 • Published • 88
Collections
Discover the best community collections!
Collections including paper arxiv:2504.16084
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SQL-R1: Training Natural Language to SQL Reasoning Model By Reinforcement Learning
Paper • 2504.08600 • Published • 31 -
Think-on-Graph 3.0: Efficient and Adaptive LLM Reasoning on Heterogeneous Graphs via Multi-Agent Dual-Evolving Context Retrieval
Paper • 2509.21710 • Published • 17 -
TTRL: Test-Time Reinforcement Learning
Paper • 2504.16084 • Published • 120 -
Agent Lightning: Train ANY AI Agents with Reinforcement Learning
Paper • 2508.03680 • Published • 89
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Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?
Paper • 2504.13837 • Published • 135 -
TTRL: Test-Time Reinforcement Learning
Paper • 2504.16084 • Published • 120 -
What, How, Where, and How Well? A Survey on Test-Time Scaling in Large Language Models
Paper • 2503.24235 • Published • 54 -
Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning
Paper • 2506.01939 • Published • 185
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Less is More: Recursive Reasoning with Tiny Networks
Paper • 2510.04871 • Published • 462 -
When Thoughts Meet Facts: Reusable Reasoning for Long-Context LMs
Paper • 2510.07499 • Published • 48 -
Improving Context Fidelity via Native Retrieval-Augmented Reasoning
Paper • 2509.13683 • Published • 8 -
Multimodal Iterative RAG for Knowledge-Intensive Visual Question Answering
Paper • 2509.00798 • Published • 1
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Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems
Paper • 2504.01990 • Published • 300 -
InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models
Paper • 2504.10479 • Published • 298 -
What, How, Where, and How Well? A Survey on Test-Time Scaling in Large Language Models
Paper • 2503.24235 • Published • 54 -
Seedream 3.0 Technical Report
Paper • 2504.11346 • Published • 70
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TTRL: Test-Time Reinforcement Learning
Paper • 2504.16084 • Published • 120 -
Describe Anything: Detailed Localized Image and Video Captioning
Paper • 2504.16072 • Published • 63 -
Reinforcing General Reasoning without Verifiers
Paper • 2505.21493 • Published • 26 -
REASONING GYM: Reasoning Environments for Reinforcement Learning with Verifiable Rewards
Paper • 2505.24760 • Published • 73
-
Towards General-Purpose Model-Free Reinforcement Learning
Paper • 2501.16142 • Published • 30 -
DAPO: An Open-Source LLM Reinforcement Learning System at Scale
Paper • 2503.14476 • Published • 141 -
Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?
Paper • 2504.13837 • Published • 135 -
Learning to Reason under Off-Policy Guidance
Paper • 2504.14945 • Published • 88
-
Less is More: Recursive Reasoning with Tiny Networks
Paper • 2510.04871 • Published • 462 -
When Thoughts Meet Facts: Reusable Reasoning for Long-Context LMs
Paper • 2510.07499 • Published • 48 -
Improving Context Fidelity via Native Retrieval-Augmented Reasoning
Paper • 2509.13683 • Published • 8 -
Multimodal Iterative RAG for Knowledge-Intensive Visual Question Answering
Paper • 2509.00798 • Published • 1
-
SQL-R1: Training Natural Language to SQL Reasoning Model By Reinforcement Learning
Paper • 2504.08600 • Published • 31 -
Think-on-Graph 3.0: Efficient and Adaptive LLM Reasoning on Heterogeneous Graphs via Multi-Agent Dual-Evolving Context Retrieval
Paper • 2509.21710 • Published • 17 -
TTRL: Test-Time Reinforcement Learning
Paper • 2504.16084 • Published • 120 -
Agent Lightning: Train ANY AI Agents with Reinforcement Learning
Paper • 2508.03680 • Published • 89
-
Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems
Paper • 2504.01990 • Published • 300 -
InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models
Paper • 2504.10479 • Published • 298 -
What, How, Where, and How Well? A Survey on Test-Time Scaling in Large Language Models
Paper • 2503.24235 • Published • 54 -
Seedream 3.0 Technical Report
Paper • 2504.11346 • Published • 70
-
Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?
Paper • 2504.13837 • Published • 135 -
TTRL: Test-Time Reinforcement Learning
Paper • 2504.16084 • Published • 120 -
What, How, Where, and How Well? A Survey on Test-Time Scaling in Large Language Models
Paper • 2503.24235 • Published • 54 -
Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning
Paper • 2506.01939 • Published • 185
-
TTRL: Test-Time Reinforcement Learning
Paper • 2504.16084 • Published • 120 -
Describe Anything: Detailed Localized Image and Video Captioning
Paper • 2504.16072 • Published • 63 -
Reinforcing General Reasoning without Verifiers
Paper • 2505.21493 • Published • 26 -
REASONING GYM: Reasoning Environments for Reinforcement Learning with Verifiable Rewards
Paper • 2505.24760 • Published • 73