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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 • 13 -
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:2507.07966
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M3DocRAG: Multi-modal Retrieval is What You Need for Multi-page Multi-document Understanding
Paper • 2411.04952 • Published • 30 -
Diff-2-in-1: Bridging Generation and Dense Perception with Diffusion Models
Paper • 2411.05005 • Published • 13 -
M3SciQA: A Multi-Modal Multi-Document Scientific QA Benchmark for Evaluating Foundation Models
Paper • 2411.04075 • Published • 17 -
Self-Consistency Preference Optimization
Paper • 2411.04109 • Published • 19
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UniRef++: Segment Every Reference Object in Spatial and Temporal Spaces
Paper • 2312.15715 • Published • 21 -
Spatial-MLLM: Boosting MLLM Capabilities in Visual-based Spatial Intelligence
Paper • 2505.23747 • Published • 67 -
VideoPrism: A Foundational Visual Encoder for Video Understanding
Paper • 2402.13217 • Published • 34 -
Scaling RL to Long Videos
Paper • 2507.07966 • Published • 103
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Masked Generative Video-to-Audio Transformers with Enhanced Synchronicity
Paper • 2407.10387 • Published • 8 -
Mixture-of-Transformers: A Sparse and Scalable Architecture for Multi-Modal Foundation Models
Paper • 2411.04996 • Published • 52 -
Sa2VA: Marrying SAM2 with LLaVA for Dense Grounded Understanding of Images and Videos
Paper • 2501.04001 • Published • 47 -
Scaling RL to Long Videos
Paper • 2507.07966 • Published • 103
-
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 • 13 -
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
-
M3DocRAG: Multi-modal Retrieval is What You Need for Multi-page Multi-document Understanding
Paper • 2411.04952 • Published • 30 -
Diff-2-in-1: Bridging Generation and Dense Perception with Diffusion Models
Paper • 2411.05005 • Published • 13 -
M3SciQA: A Multi-Modal Multi-Document Scientific QA Benchmark for Evaluating Foundation Models
Paper • 2411.04075 • Published • 17 -
Self-Consistency Preference Optimization
Paper • 2411.04109 • Published • 19
-
Masked Generative Video-to-Audio Transformers with Enhanced Synchronicity
Paper • 2407.10387 • Published • 8 -
Mixture-of-Transformers: A Sparse and Scalable Architecture for Multi-Modal Foundation Models
Paper • 2411.04996 • Published • 52 -
Sa2VA: Marrying SAM2 with LLaVA for Dense Grounded Understanding of Images and Videos
Paper • 2501.04001 • Published • 47 -
Scaling RL to Long Videos
Paper • 2507.07966 • Published • 103
-
UniRef++: Segment Every Reference Object in Spatial and Temporal Spaces
Paper • 2312.15715 • Published • 21 -
Spatial-MLLM: Boosting MLLM Capabilities in Visual-based Spatial Intelligence
Paper • 2505.23747 • Published • 67 -
VideoPrism: A Foundational Visual Encoder for Video Understanding
Paper • 2402.13217 • Published • 34 -
Scaling RL to Long Videos
Paper • 2507.07966 • Published • 103