Collections
Discover the best community collections!
Collections including paper arxiv:2510.12747
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Demystifying Reinforcement Learning in Agentic Reasoning
Paper • 2510.11701 • Published • 31 -
Self-Improving LLM Agents at Test-Time
Paper • 2510.07841 • Published • 9 -
Making Mathematical Reasoning Adaptive
Paper • 2510.04617 • Published • 22 -
DocReward: A Document Reward Model for Structuring and Stylizing
Paper • 2510.11391 • Published • 27
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EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 29 -
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
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Sa2VA: Marrying SAM2 with LLaVA for Dense Grounded Understanding of Images and Videos
Paper • 2501.04001 • Published • 47 -
LLaVA-Mini: Efficient Image and Video Large Multimodal Models with One Vision Token
Paper • 2501.03895 • Published • 52 -
An Empirical Study of Autoregressive Pre-training from Videos
Paper • 2501.05453 • Published • 41 -
MatchAnything: Universal Cross-Modality Image Matching with Large-Scale Pre-Training
Paper • 2501.07556 • Published • 7
-
Demystifying Reinforcement Learning in Agentic Reasoning
Paper • 2510.11701 • Published • 31 -
Self-Improving LLM Agents at Test-Time
Paper • 2510.07841 • Published • 9 -
Making Mathematical Reasoning Adaptive
Paper • 2510.04617 • Published • 22 -
DocReward: A Document Reward Model for Structuring and Stylizing
Paper • 2510.11391 • Published • 27
-
Sa2VA: Marrying SAM2 with LLaVA for Dense Grounded Understanding of Images and Videos
Paper • 2501.04001 • Published • 47 -
LLaVA-Mini: Efficient Image and Video Large Multimodal Models with One Vision Token
Paper • 2501.03895 • Published • 52 -
An Empirical Study of Autoregressive Pre-training from Videos
Paper • 2501.05453 • Published • 41 -
MatchAnything: Universal Cross-Modality Image Matching with Large-Scale Pre-Training
Paper • 2501.07556 • Published • 7
-
EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 29 -
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