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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
Collections
Discover the best community collections!
Collections including paper arxiv:2403.07508
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ReTool: Reinforcement Learning for Strategic Tool Use in LLMs
Paper • 2504.11536 • Published • 63 -
Reflect, Retry, Reward: Self-Improving LLMs via Reinforcement Learning
Paper • 2505.24726 • Published • 277 -
Multimodal Chain-of-Thought Reasoning: A Comprehensive Survey
Paper • 2503.12605 • Published • 35 -
MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention
Paper • 2506.13585 • Published • 273
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How Far Are We from Intelligent Visual Deductive Reasoning?
Paper • 2403.04732 • Published • 21 -
MoAI: Mixture of All Intelligence for Large Language and Vision Models
Paper • 2403.07508 • Published • 77 -
DragAnything: Motion Control for Anything using Entity Representation
Paper • 2403.07420 • Published • 14 -
Learning and Leveraging World Models in Visual Representation Learning
Paper • 2403.00504 • Published • 33
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Motion Mamba: Efficient and Long Sequence Motion Generation with Hierarchical and Bidirectional Selective SSM
Paper • 2403.07487 • Published • 16 -
MoAI: Mixture of All Intelligence for Large Language and Vision Models
Paper • 2403.07508 • Published • 77 -
VLOGGER: Multimodal Diffusion for Embodied Avatar Synthesis
Paper • 2403.08764 • Published • 36
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Scaling Instruction-Finetuned Language Models
Paper • 2210.11416 • Published • 7 -
Mamba: Linear-Time Sequence Modeling with Selective State Spaces
Paper • 2312.00752 • Published • 148 -
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Paper • 2403.05530 • Published • 65 -
Yi: Open Foundation Models by 01.AI
Paper • 2403.04652 • Published • 65
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Woodpecker: Hallucination Correction for Multimodal Large Language Models
Paper • 2310.16045 • Published • 17 -
HallusionBench: You See What You Think? Or You Think What You See? An Image-Context Reasoning Benchmark Challenging for GPT-4V(ision), LLaVA-1.5, and Other Multi-modality Models
Paper • 2310.14566 • Published • 27 -
SILC: Improving Vision Language Pretraining with Self-Distillation
Paper • 2310.13355 • Published • 9 -
Conditional Diffusion Distillation
Paper • 2310.01407 • Published • 20
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Visual Fact Checker: Enabling High-Fidelity Detailed Caption Generation
Paper • 2404.19752 • Published • 24 -
How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites
Paper • 2404.16821 • Published • 58 -
MoAI: Mixture of All Intelligence for Large Language and Vision Models
Paper • 2403.07508 • Published • 77 -
MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training
Paper • 2403.09611 • Published • 129
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TinyLLaVA: A Framework of Small-scale Large Multimodal Models
Paper • 2402.14289 • Published • 20 -
ImageBind: One Embedding Space To Bind Them All
Paper • 2305.05665 • Published • 6 -
DocLLM: A layout-aware generative language model for multimodal document understanding
Paper • 2401.00908 • Published • 189 -
Multimodal Contrastive Learning with LIMoE: the Language-Image Mixture of Experts
Paper • 2206.02770 • Published • 4
-
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
-
Woodpecker: Hallucination Correction for Multimodal Large Language Models
Paper • 2310.16045 • Published • 17 -
HallusionBench: You See What You Think? Or You Think What You See? An Image-Context Reasoning Benchmark Challenging for GPT-4V(ision), LLaVA-1.5, and Other Multi-modality Models
Paper • 2310.14566 • Published • 27 -
SILC: Improving Vision Language Pretraining with Self-Distillation
Paper • 2310.13355 • Published • 9 -
Conditional Diffusion Distillation
Paper • 2310.01407 • Published • 20
-
ReTool: Reinforcement Learning for Strategic Tool Use in LLMs
Paper • 2504.11536 • Published • 63 -
Reflect, Retry, Reward: Self-Improving LLMs via Reinforcement Learning
Paper • 2505.24726 • Published • 277 -
Multimodal Chain-of-Thought Reasoning: A Comprehensive Survey
Paper • 2503.12605 • Published • 35 -
MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention
Paper • 2506.13585 • Published • 273
-
Visual Fact Checker: Enabling High-Fidelity Detailed Caption Generation
Paper • 2404.19752 • Published • 24 -
How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites
Paper • 2404.16821 • Published • 58 -
MoAI: Mixture of All Intelligence for Large Language and Vision Models
Paper • 2403.07508 • Published • 77 -
MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training
Paper • 2403.09611 • Published • 129
-
How Far Are We from Intelligent Visual Deductive Reasoning?
Paper • 2403.04732 • Published • 21 -
MoAI: Mixture of All Intelligence for Large Language and Vision Models
Paper • 2403.07508 • Published • 77 -
DragAnything: Motion Control for Anything using Entity Representation
Paper • 2403.07420 • Published • 14 -
Learning and Leveraging World Models in Visual Representation Learning
Paper • 2403.00504 • Published • 33
-
Motion Mamba: Efficient and Long Sequence Motion Generation with Hierarchical and Bidirectional Selective SSM
Paper • 2403.07487 • Published • 16 -
MoAI: Mixture of All Intelligence for Large Language and Vision Models
Paper • 2403.07508 • Published • 77 -
VLOGGER: Multimodal Diffusion for Embodied Avatar Synthesis
Paper • 2403.08764 • Published • 36
-
Scaling Instruction-Finetuned Language Models
Paper • 2210.11416 • Published • 7 -
Mamba: Linear-Time Sequence Modeling with Selective State Spaces
Paper • 2312.00752 • Published • 148 -
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Paper • 2403.05530 • Published • 65 -
Yi: Open Foundation Models by 01.AI
Paper • 2403.04652 • Published • 65
-
TinyLLaVA: A Framework of Small-scale Large Multimodal Models
Paper • 2402.14289 • Published • 20 -
ImageBind: One Embedding Space To Bind Them All
Paper • 2305.05665 • Published • 6 -
DocLLM: A layout-aware generative language model for multimodal document understanding
Paper • 2401.00908 • Published • 189 -
Multimodal Contrastive Learning with LIMoE: the Language-Image Mixture of Experts
Paper • 2206.02770 • Published • 4