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Low-probability Tokens Sustain Exploration in Reinforcement Learning with Verifiable Reward
Paper • 2510.03222 • Published • 45 -
In-the-Flow Agentic System Optimization for Effective Planning and Tool Use
Paper • 2510.05592 • Published • 94 -
Less is More: Recursive Reasoning with Tiny Networks
Paper • 2510.04871 • Published • 461 -
Multi-Agent Tool-Integrated Policy Optimization
Paper • 2510.04678 • Published • 30
Collections
Discover the best community collections!
Collections including paper arxiv:2509.22576
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EPO: Entropy-regularized Policy Optimization for LLM Agents Reinforcement Learning
Paper • 2509.22576 • Published • 132 -
AgentBench: Evaluating LLMs as Agents
Paper • 2308.03688 • Published • 25 -
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
Paper • 1910.01108 • Published • 20 -
Direct Preference Optimization: Your Language Model is Secretly a Reward Model
Paper • 2305.18290 • Published • 63
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Open Data Synthesis For Deep Research
Paper • 2509.00375 • Published • 68 -
Beyond Correctness: Harmonizing Process and Outcome Rewards through RL Training
Paper • 2509.03403 • Published • 21 -
LMEnt: A Suite for Analyzing Knowledge in Language Models from Pretraining Data to Representations
Paper • 2509.03405 • Published • 23 -
SATQuest: A Verifier for Logical Reasoning Evaluation and Reinforcement Fine-Tuning of LLMs
Paper • 2509.00930 • Published • 4
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lusxvr/nanoVLM-222M
Image-Text-to-Text • 0.2B • Updated • 266 • 96 -
Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning
Paper • 2503.09516 • Published • 36 -
AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time
Paper • 2505.24863 • Published • 97 -
QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning
Paper • 2505.17667 • Published • 88
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HALO: Hierarchical Autonomous Logic-Oriented Orchestration for Multi-Agent LLM Systems
Paper • 2505.13516 • Published -
EPO: Entropy-regularized Policy Optimization for LLM Agents Reinforcement Learning
Paper • 2509.22576 • Published • 132 -
AutoML-Agent: A Multi-Agent LLM Framework for Full-Pipeline AutoML
Paper • 2410.02958 • Published
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EPO: Entropy-regularized Policy Optimization for LLM Agents Reinforcement Learning
Paper • 2509.22576 • Published • 132 -
No Prompt Left Behind: Exploiting Zero-Variance Prompts in LLM Reinforcement Learning via Entropy-Guided Advantage Shaping
Paper • 2509.21880 • Published • 51 -
DITING: A Multi-Agent Evaluation Framework for Benchmarking Web Novel Translation
Paper • 2510.09116 • Published • 95
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Agent Lightning: Train ANY AI Agents with Reinforcement Learning
Paper • 2508.03680 • Published • 87 -
Training Long-Context, Multi-Turn Software Engineering Agents with Reinforcement Learning
Paper • 2508.03501 • Published • 56 -
SEAgent: Self-Evolving Computer Use Agent with Autonomous Learning from Experience
Paper • 2508.04700 • Published • 52 -
RoboMemory: A Brain-inspired Multi-memory Agentic Framework for Lifelong Learning in Physical Embodied Systems
Paper • 2508.01415 • Published • 7
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Diffusion Augmented Agents: A Framework for Efficient Exploration and Transfer Learning
Paper • 2407.20798 • Published • 24 -
Offline Reinforcement Learning for LLM Multi-Step Reasoning
Paper • 2412.16145 • Published • 38 -
REINFORCE++: A Simple and Efficient Approach for Aligning Large Language Models
Paper • 2501.03262 • Published • 102 -
SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software Evolution
Paper • 2502.18449 • Published • 75
-
Low-probability Tokens Sustain Exploration in Reinforcement Learning with Verifiable Reward
Paper • 2510.03222 • Published • 45 -
In-the-Flow Agentic System Optimization for Effective Planning and Tool Use
Paper • 2510.05592 • Published • 94 -
Less is More: Recursive Reasoning with Tiny Networks
Paper • 2510.04871 • Published • 461 -
Multi-Agent Tool-Integrated Policy Optimization
Paper • 2510.04678 • Published • 30
-
HALO: Hierarchical Autonomous Logic-Oriented Orchestration for Multi-Agent LLM Systems
Paper • 2505.13516 • Published -
EPO: Entropy-regularized Policy Optimization for LLM Agents Reinforcement Learning
Paper • 2509.22576 • Published • 132 -
AutoML-Agent: A Multi-Agent LLM Framework for Full-Pipeline AutoML
Paper • 2410.02958 • Published
-
EPO: Entropy-regularized Policy Optimization for LLM Agents Reinforcement Learning
Paper • 2509.22576 • Published • 132 -
AgentBench: Evaluating LLMs as Agents
Paper • 2308.03688 • Published • 25 -
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
Paper • 1910.01108 • Published • 20 -
Direct Preference Optimization: Your Language Model is Secretly a Reward Model
Paper • 2305.18290 • Published • 63
-
EPO: Entropy-regularized Policy Optimization for LLM Agents Reinforcement Learning
Paper • 2509.22576 • Published • 132 -
No Prompt Left Behind: Exploiting Zero-Variance Prompts in LLM Reinforcement Learning via Entropy-Guided Advantage Shaping
Paper • 2509.21880 • Published • 51 -
DITING: A Multi-Agent Evaluation Framework for Benchmarking Web Novel Translation
Paper • 2510.09116 • Published • 95
-
Open Data Synthesis For Deep Research
Paper • 2509.00375 • Published • 68 -
Beyond Correctness: Harmonizing Process and Outcome Rewards through RL Training
Paper • 2509.03403 • Published • 21 -
LMEnt: A Suite for Analyzing Knowledge in Language Models from Pretraining Data to Representations
Paper • 2509.03405 • Published • 23 -
SATQuest: A Verifier for Logical Reasoning Evaluation and Reinforcement Fine-Tuning of LLMs
Paper • 2509.00930 • Published • 4
-
Agent Lightning: Train ANY AI Agents with Reinforcement Learning
Paper • 2508.03680 • Published • 87 -
Training Long-Context, Multi-Turn Software Engineering Agents with Reinforcement Learning
Paper • 2508.03501 • Published • 56 -
SEAgent: Self-Evolving Computer Use Agent with Autonomous Learning from Experience
Paper • 2508.04700 • Published • 52 -
RoboMemory: A Brain-inspired Multi-memory Agentic Framework for Lifelong Learning in Physical Embodied Systems
Paper • 2508.01415 • Published • 7
-
lusxvr/nanoVLM-222M
Image-Text-to-Text • 0.2B • Updated • 266 • 96 -
Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning
Paper • 2503.09516 • Published • 36 -
AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time
Paper • 2505.24863 • Published • 97 -
QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning
Paper • 2505.17667 • Published • 88
-
Diffusion Augmented Agents: A Framework for Efficient Exploration and Transfer Learning
Paper • 2407.20798 • Published • 24 -
Offline Reinforcement Learning for LLM Multi-Step Reasoning
Paper • 2412.16145 • Published • 38 -
REINFORCE++: A Simple and Efficient Approach for Aligning Large Language Models
Paper • 2501.03262 • Published • 102 -
SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software Evolution
Paper • 2502.18449 • Published • 75