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Multi-Agent Computer Use
Paper • 2606.01533 • Published • 7 -
OpenSkill: Open-World Self-Evolution for LLM Agents
Paper • 2606.06741 • Published • 29 -
Socratic-SWE: Self-Evolving Coding Agents via Trace-Derived Agent Skills
Paper • 2606.07412 • Published • 12 -
Bayesian-Agent: Posterior-Guided Skill Evolution for LLM Agent Harnesses
Paper • 2606.08348 • Published • 16
Collections
Discover the best community collections!
Collections including paper arxiv:2606.09821
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LTX-2: Efficient Joint Audio-Visual Foundation Model
Paper • 2601.03233 • Published • 184 -
MHLA: Restoring Expressivity of Linear Attention via Token-Level Multi-Head
Paper • 2601.07832 • Published • 53 -
Motion Attribution for Video Generation
Paper • 2601.08828 • Published • 72 -
Post-LayerNorm Is Back: Stable, ExpressivE, and Deep
Paper • 2601.19895 • Published • 27
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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 • 103 -
SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software Evolution
Paper • 2502.18449 • Published • 75
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Why Fine-Tuning Encourages Hallucinations and How to Fix It
Paper • 2604.15574 • Published • 26 -
Tuna-2: Pixel Embeddings Beat Vision Encoders for Multimodal Understanding and Generation
Paper • 2604.24763 • Published • 71 -
Programming with Data: Test-Driven Data Engineering for Self-Improving LLMs from Raw Corpora
Paper • 2604.24819 • Published • 91 -
GLM-5V-Turbo: Toward a Native Foundation Model for Multimodal Agents
Paper • 2604.26752 • Published • 112
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Meta-Awareness Enhances Reasoning Models: Self-Alignment Reinforcement Learning
Paper • 2510.03259 • Published • 57 -
Hybrid Reinforcement: When Reward Is Sparse, It's Better to Be Dense
Paper • 2510.07242 • Published • 30 -
First Try Matters: Revisiting the Role of Reflection in Reasoning Models
Paper • 2510.08308 • Published • 24 -
Low-probability Tokens Sustain Exploration in Reinforcement Learning with Verifiable Reward
Paper • 2510.03222 • Published • 76
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Multi-Agent Computer Use
Paper • 2606.01533 • Published • 7 -
OpenSkill: Open-World Self-Evolution for LLM Agents
Paper • 2606.06741 • Published • 29 -
Socratic-SWE: Self-Evolving Coding Agents via Trace-Derived Agent Skills
Paper • 2606.07412 • Published • 12 -
Bayesian-Agent: Posterior-Guided Skill Evolution for LLM Agent Harnesses
Paper • 2606.08348 • Published • 16
-
Why Fine-Tuning Encourages Hallucinations and How to Fix It
Paper • 2604.15574 • Published • 26 -
Tuna-2: Pixel Embeddings Beat Vision Encoders for Multimodal Understanding and Generation
Paper • 2604.24763 • Published • 71 -
Programming with Data: Test-Driven Data Engineering for Self-Improving LLMs from Raw Corpora
Paper • 2604.24819 • Published • 91 -
GLM-5V-Turbo: Toward a Native Foundation Model for Multimodal Agents
Paper • 2604.26752 • Published • 112
-
LTX-2: Efficient Joint Audio-Visual Foundation Model
Paper • 2601.03233 • Published • 184 -
MHLA: Restoring Expressivity of Linear Attention via Token-Level Multi-Head
Paper • 2601.07832 • Published • 53 -
Motion Attribution for Video Generation
Paper • 2601.08828 • Published • 72 -
Post-LayerNorm Is Back: Stable, ExpressivE, and Deep
Paper • 2601.19895 • Published • 27
-
Meta-Awareness Enhances Reasoning Models: Self-Alignment Reinforcement Learning
Paper • 2510.03259 • Published • 57 -
Hybrid Reinforcement: When Reward Is Sparse, It's Better to Be Dense
Paper • 2510.07242 • Published • 30 -
First Try Matters: Revisiting the Role of Reflection in Reasoning Models
Paper • 2510.08308 • Published • 24 -
Low-probability Tokens Sustain Exploration in Reinforcement Learning with Verifiable Reward
Paper • 2510.03222 • Published • 76
-
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 • 103 -
SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software Evolution
Paper • 2502.18449 • Published • 75