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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:2504.06263
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ReZero: Enhancing LLM search ability by trying one-more-time
Paper • 2504.11001 • Published • 15 -
FonTS: Text Rendering with Typography and Style Controls
Paper • 2412.00136 • Published • 1 -
GenEx: Generating an Explorable World
Paper • 2412.09624 • Published • 98 -
Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference
Paper • 2412.13663 • Published • 154
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Neural LightRig: Unlocking Accurate Object Normal and Material Estimation with Multi-Light Diffusion
Paper • 2412.09593 • Published • 18 -
CLEAR: Conv-Like Linearization Revs Pre-Trained Diffusion Transformers Up
Paper • 2412.16112 • Published • 23 -
Thinking in Space: How Multimodal Large Language Models See, Remember, and Recall Spaces
Paper • 2412.14171 • Published • 24 -
DiffSensei: Bridging Multi-Modal LLMs and Diffusion Models for Customized Manga Generation
Paper • 2412.07589 • Published • 49
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MotionBench: Benchmarking and Improving Fine-grained Video Motion Understanding for Vision Language Models
Paper • 2501.02955 • Published • 45 -
2.5 Years in Class: A Multimodal Textbook for Vision-Language Pretraining
Paper • 2501.00958 • Published • 107 -
MMVU: Measuring Expert-Level Multi-Discipline Video Understanding
Paper • 2501.12380 • Published • 86 -
VideoWorld: Exploring Knowledge Learning from Unlabeled Videos
Paper • 2501.09781 • Published • 29
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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
-
ReZero: Enhancing LLM search ability by trying one-more-time
Paper • 2504.11001 • Published • 15 -
FonTS: Text Rendering with Typography and Style Controls
Paper • 2412.00136 • Published • 1 -
GenEx: Generating an Explorable World
Paper • 2412.09624 • Published • 98 -
Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference
Paper • 2412.13663 • Published • 154
-
Neural LightRig: Unlocking Accurate Object Normal and Material Estimation with Multi-Light Diffusion
Paper • 2412.09593 • Published • 18 -
CLEAR: Conv-Like Linearization Revs Pre-Trained Diffusion Transformers Up
Paper • 2412.16112 • Published • 23 -
Thinking in Space: How Multimodal Large Language Models See, Remember, and Recall Spaces
Paper • 2412.14171 • Published • 24 -
DiffSensei: Bridging Multi-Modal LLMs and Diffusion Models for Customized Manga Generation
Paper • 2412.07589 • Published • 49
-
MotionBench: Benchmarking and Improving Fine-grained Video Motion Understanding for Vision Language Models
Paper • 2501.02955 • Published • 45 -
2.5 Years in Class: A Multimodal Textbook for Vision-Language Pretraining
Paper • 2501.00958 • Published • 107 -
MMVU: Measuring Expert-Level Multi-Discipline Video Understanding
Paper • 2501.12380 • Published • 86 -
VideoWorld: Exploring Knowledge Learning from Unlabeled Videos
Paper • 2501.09781 • Published • 29