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Reflect, Retry, Reward: Self-Improving LLMs via Reinforcement Learning
Paper • 2505.24726 • Published • 273 -
Reinforcement Pre-Training
Paper • 2506.08007 • Published • 260 -
GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning
Paper • 2507.01006 • Published • 236 -
A Survey of Context Engineering for Large Language Models
Paper • 2507.13334 • Published • 256
Collections
Discover the best community collections!
Collections including paper arxiv:2509.13312
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Revisit Large-Scale Image-Caption Data in Pre-training Multimodal Foundation Models
Paper • 2410.02740 • Published • 54 -
From Code to Correctness: Closing the Last Mile of Code Generation with Hierarchical Debugging
Paper • 2410.01215 • Published • 35 -
Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Multimodal Models
Paper • 2409.17146 • Published • 121 -
EuroLLM: Multilingual Language Models for Europe
Paper • 2409.16235 • Published • 27
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Think Before Recommend: Unleashing the Latent Reasoning Power for Sequential Recommendation
Paper • 2503.22675 • Published • 36 -
Exploring Data Scaling Trends and Effects in Reinforcement Learning from Human Feedback
Paper • 2503.22230 • Published • 45 -
ReSum: Unlocking Long-Horizon Search Intelligence via Context Summarization
Paper • 2509.13313 • Published • 72 -
WebResearcher: Unleashing unbounded reasoning capability in Long-Horizon Agents
Paper • 2509.13309 • Published • 66
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AgentOhana: Design Unified Data and Training Pipeline for Effective Agent Learning
Paper • 2402.15506 • Published • 18 -
AutoWebGLM: Bootstrap And Reinforce A Large Language Model-based Web Navigating Agent
Paper • 2404.03648 • Published • 29 -
Similarity is Not All You Need: Endowing Retrieval Augmented Generation with Multi Layered Thoughts
Paper • 2405.19893 • Published • 33 -
Parrot: Efficient Serving of LLM-based Applications with Semantic Variable
Paper • 2405.19888 • Published • 7
-
Reflect, Retry, Reward: Self-Improving LLMs via Reinforcement Learning
Paper • 2505.24726 • Published • 273 -
Reinforcement Pre-Training
Paper • 2506.08007 • Published • 260 -
GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning
Paper • 2507.01006 • Published • 236 -
A Survey of Context Engineering for Large Language Models
Paper • 2507.13334 • Published • 256
-
Think Before Recommend: Unleashing the Latent Reasoning Power for Sequential Recommendation
Paper • 2503.22675 • Published • 36 -
Exploring Data Scaling Trends and Effects in Reinforcement Learning from Human Feedback
Paper • 2503.22230 • Published • 45 -
ReSum: Unlocking Long-Horizon Search Intelligence via Context Summarization
Paper • 2509.13313 • Published • 72 -
WebResearcher: Unleashing unbounded reasoning capability in Long-Horizon Agents
Paper • 2509.13309 • Published • 66
-
Revisit Large-Scale Image-Caption Data in Pre-training Multimodal Foundation Models
Paper • 2410.02740 • Published • 54 -
From Code to Correctness: Closing the Last Mile of Code Generation with Hierarchical Debugging
Paper • 2410.01215 • Published • 35 -
Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Multimodal Models
Paper • 2409.17146 • Published • 121 -
EuroLLM: Multilingual Language Models for Europe
Paper • 2409.16235 • Published • 27
-
AgentOhana: Design Unified Data and Training Pipeline for Effective Agent Learning
Paper • 2402.15506 • Published • 18 -
AutoWebGLM: Bootstrap And Reinforce A Large Language Model-based Web Navigating Agent
Paper • 2404.03648 • Published • 29 -
Similarity is Not All You Need: Endowing Retrieval Augmented Generation with Multi Layered Thoughts
Paper • 2405.19893 • Published • 33 -
Parrot: Efficient Serving of LLM-based Applications with Semantic Variable
Paper • 2405.19888 • Published • 7