- 
	
	
	
EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 28 - 
	
	
	
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models
Paper • 2402.03749 • Published • 14 - 
	
	
	
ScreenAI: A Vision-Language Model for UI and Infographics Understanding
Paper • 2402.04615 • Published • 44 - 
	
	
	
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 23 
Collections
Discover the best community collections!
Collections including paper arxiv:2509.13310 
						
					
				- 
	
	
	
Agent Learning via Early Experience
Paper • 2510.08558 • Published • 258 - 
	
	
	
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Paper • 2509.02547 • Published • 220 - 
	
	
	
Scaling Agents via Continual Pre-training
Paper • 2509.13310 • Published • 113 - 
	
	
	
Agent Lightning: Train ANY AI Agents with Reinforcement Learning
Paper • 2508.03680 • Published • 93 
- 
	
	
	
Sharing is Caring: Efficient LM Post-Training with Collective RL Experience Sharing
Paper • 2509.08721 • Published • 672 - 
	
	
	
A.S.E: A Repository-Level Benchmark for Evaluating Security in AI-Generated Code
Paper • 2508.18106 • Published • 342 - 
	
	
	
VLA-Adapter: An Effective Paradigm for Tiny-Scale Vision-Language-Action Model
Paper • 2509.09372 • Published • 235 - 
	
	
	
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Paper • 2509.02547 • Published • 220 
- 
	
	
	
Reflect, Retry, Reward: Self-Improving LLMs via Reinforcement Learning
Paper • 2505.24726 • Published • 274 - 
	
	
	
Reinforcement Pre-Training
Paper • 2506.08007 • Published • 262 - 
	
	
	
GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning
Paper • 2507.01006 • Published • 237 - 
	
	
	
A Survey of Context Engineering for Large Language Models
Paper • 2507.13334 • Published • 258 
- 
	
	
	
FastVLM: Efficient Vision Encoding for Vision Language Models
Paper • 2412.13303 • Published • 70 - 
	
	
	
rStar2-Agent: Agentic Reasoning Technical Report
Paper • 2508.20722 • Published • 113 - 
	
	
	
AgentScope 1.0: A Developer-Centric Framework for Building Agentic Applications
Paper • 2508.16279 • Published • 52 - 
	
	
	
OmniWorld: A Multi-Domain and Multi-Modal Dataset for 4D World Modeling
Paper • 2509.12201 • Published • 103 
- 
	
	
	
Scaling Agents via Continual Pre-training
Paper • 2509.13310 • Published • 113 - 
	
	
	
WebSailor-V2: Bridging the Chasm to Proprietary Agents via Synthetic Data and Scalable Reinforcement Learning
Paper • 2509.13305 • Published • 89 - 
	
	
	
In-the-Flow Agentic System Optimization for Effective Planning and Tool Use
Paper • 2510.05592 • Published • 96 - 
	
	
	
Explore to Evolve: Scaling Evolved Aggregation Logic via Proactive Online Exploration for Deep Research Agents
Paper • 2510.14438 • Published • 13 
- 
	
	
	
WebShaper: Agentically Data Synthesizing via Information-Seeking Formalization
Paper • 2507.15061 • Published • 59 - 
	
	
	
WebDancer: Towards Autonomous Information Seeking Agency
Paper • 2505.22648 • Published • 33 - 
	
	
	
ReSum: Unlocking Long-Horizon Search Intelligence via Context Summarization
Paper • 2509.13313 • Published • 78 - 
	
	
	
WebSailor-V2: Bridging the Chasm to Proprietary Agents via Synthetic Data and Scalable Reinforcement Learning
Paper • 2509.13305 • Published • 89 
- 
	
	
	
Mind2Web 2: Evaluating Agentic Search with Agent-as-a-Judge
Paper • 2506.21506 • Published • 51 - 
	
	
	
Distilling LLM Agent into Small Models with Retrieval and Code Tools
Paper • 2505.17612 • Published • 81 - 
	
	
	
Efficient Agent Training for Computer Use
Paper • 2505.13909 • Published • 44 - 
	
	
	
Scaling Agents via Continual Pre-training
Paper • 2509.13310 • Published • 113 
- 
	
	
	
EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 28 - 
	
	
	
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models
Paper • 2402.03749 • Published • 14 - 
	
	
	
ScreenAI: A Vision-Language Model for UI and Infographics Understanding
Paper • 2402.04615 • Published • 44 - 
	
	
	
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 23 
- 
	
	
	
Agent Learning via Early Experience
Paper • 2510.08558 • Published • 258 - 
	
	
	
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Paper • 2509.02547 • Published • 220 - 
	
	
	
Scaling Agents via Continual Pre-training
Paper • 2509.13310 • Published • 113 - 
	
	
	
Agent Lightning: Train ANY AI Agents with Reinforcement Learning
Paper • 2508.03680 • Published • 93 
- 
	
	
	
Scaling Agents via Continual Pre-training
Paper • 2509.13310 • Published • 113 - 
	
	
	
WebSailor-V2: Bridging the Chasm to Proprietary Agents via Synthetic Data and Scalable Reinforcement Learning
Paper • 2509.13305 • Published • 89 - 
	
	
	
In-the-Flow Agentic System Optimization for Effective Planning and Tool Use
Paper • 2510.05592 • Published • 96 - 
	
	
	
Explore to Evolve: Scaling Evolved Aggregation Logic via Proactive Online Exploration for Deep Research Agents
Paper • 2510.14438 • Published • 13 
- 
	
	
	
Sharing is Caring: Efficient LM Post-Training with Collective RL Experience Sharing
Paper • 2509.08721 • Published • 672 - 
	
	
	
A.S.E: A Repository-Level Benchmark for Evaluating Security in AI-Generated Code
Paper • 2508.18106 • Published • 342 - 
	
	
	
VLA-Adapter: An Effective Paradigm for Tiny-Scale Vision-Language-Action Model
Paper • 2509.09372 • Published • 235 - 
	
	
	
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Paper • 2509.02547 • Published • 220 
- 
	
	
	
WebShaper: Agentically Data Synthesizing via Information-Seeking Formalization
Paper • 2507.15061 • Published • 59 - 
	
	
	
WebDancer: Towards Autonomous Information Seeking Agency
Paper • 2505.22648 • Published • 33 - 
	
	
	
ReSum: Unlocking Long-Horizon Search Intelligence via Context Summarization
Paper • 2509.13313 • Published • 78 - 
	
	
	
WebSailor-V2: Bridging the Chasm to Proprietary Agents via Synthetic Data and Scalable Reinforcement Learning
Paper • 2509.13305 • Published • 89 
- 
	
	
	
Reflect, Retry, Reward: Self-Improving LLMs via Reinforcement Learning
Paper • 2505.24726 • Published • 274 - 
	
	
	
Reinforcement Pre-Training
Paper • 2506.08007 • Published • 262 - 
	
	
	
GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning
Paper • 2507.01006 • Published • 237 - 
	
	
	
A Survey of Context Engineering for Large Language Models
Paper • 2507.13334 • Published • 258 
- 
	
	
	
FastVLM: Efficient Vision Encoding for Vision Language Models
Paper • 2412.13303 • Published • 70 - 
	
	
	
rStar2-Agent: Agentic Reasoning Technical Report
Paper • 2508.20722 • Published • 113 - 
	
	
	
AgentScope 1.0: A Developer-Centric Framework for Building Agentic Applications
Paper • 2508.16279 • Published • 52 - 
	
	
	
OmniWorld: A Multi-Domain and Multi-Modal Dataset for 4D World Modeling
Paper • 2509.12201 • Published • 103 
- 
	
	
	
Mind2Web 2: Evaluating Agentic Search with Agent-as-a-Judge
Paper • 2506.21506 • Published • 51 - 
	
	
	
Distilling LLM Agent into Small Models with Retrieval and Code Tools
Paper • 2505.17612 • Published • 81 - 
	
	
	
Efficient Agent Training for Computer Use
Paper • 2505.13909 • Published • 44 - 
	
	
	
Scaling Agents via Continual Pre-training
Paper • 2509.13310 • Published • 113