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Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 23 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 85 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 151 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25
Collections
Discover the best community collections!
Collections including paper arxiv:2506.16406
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TreeRanker: Fast and Model-agnostic Ranking System for Code Suggestions in IDEs
Paper • 2508.02455 • Published • 3 -
Drag-and-Drop LLMs: Zero-Shot Prompt-to-Weights
Paper • 2506.16406 • Published • 127 -
Key-Augmented Neural Triggers for Knowledge Sharing
Paper • 2508.03340 • Published -
Next Edit Prediction: Learning to Predict Code Edits from Context and Interaction History
Paper • 2508.10074 • Published
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Lingshu: A Generalist Foundation Model for Unified Multimodal Medical Understanding and Reasoning
Paper • 2506.07044 • Published • 114 -
ReasonMed: A 370K Multi-Agent Generated Dataset for Advancing Medical Reasoning
Paper • 2506.09513 • Published • 100 -
AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time
Paper • 2505.24863 • Published • 97 -
Seedance 1.0: Exploring the Boundaries of Video Generation Models
Paper • 2506.09113 • Published • 104
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Snowflake/Arctic-Text2SQL-R1-7B
8B • Updated • 13.3k • 56 -
Reflect, Retry, Reward: Self-Improving LLMs via Reinforcement Learning
Paper • 2505.24726 • Published • 276 -
Reinforcement Pre-Training
Paper • 2506.08007 • Published • 262 -
Drag-and-Drop LLMs: Zero-Shot Prompt-to-Weights
Paper • 2506.16406 • Published • 127
-
Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 23 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 85 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 151 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25
-
TreeRanker: Fast and Model-agnostic Ranking System for Code Suggestions in IDEs
Paper • 2508.02455 • Published • 3 -
Drag-and-Drop LLMs: Zero-Shot Prompt-to-Weights
Paper • 2506.16406 • Published • 127 -
Key-Augmented Neural Triggers for Knowledge Sharing
Paper • 2508.03340 • Published -
Next Edit Prediction: Learning to Predict Code Edits from Context and Interaction History
Paper • 2508.10074 • Published
-
Snowflake/Arctic-Text2SQL-R1-7B
8B • Updated • 13.3k • 56 -
Reflect, Retry, Reward: Self-Improving LLMs via Reinforcement Learning
Paper • 2505.24726 • Published • 276 -
Reinforcement Pre-Training
Paper • 2506.08007 • Published • 262 -
Drag-and-Drop LLMs: Zero-Shot Prompt-to-Weights
Paper • 2506.16406 • Published • 127
-
Lingshu: A Generalist Foundation Model for Unified Multimodal Medical Understanding and Reasoning
Paper • 2506.07044 • Published • 114 -
ReasonMed: A 370K Multi-Agent Generated Dataset for Advancing Medical Reasoning
Paper • 2506.09513 • Published • 100 -
AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time
Paper • 2505.24863 • Published • 97 -
Seedance 1.0: Exploring the Boundaries of Video Generation Models
Paper • 2506.09113 • Published • 104