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iVideoGPT: Interactive VideoGPTs are Scalable World Models
Paper • 2405.15223 • Published • 17 -
Meteor: Mamba-based Traversal of Rationale for Large Language and Vision Models
Paper • 2405.15574 • Published • 55 -
An Introduction to Vision-Language Modeling
Paper • 2405.17247 • Published • 90 -
Matryoshka Multimodal Models
Paper • 2405.17430 • Published • 34
Collections
Discover the best community collections!
Collections including paper arxiv:2501.03895
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The Evolution of Multimodal Model Architectures
Paper • 2405.17927 • Published • 1 -
What matters when building vision-language models?
Paper • 2405.02246 • Published • 103 -
Efficient Architectures for High Resolution Vision-Language Models
Paper • 2501.02584 • Published -
Building and better understanding vision-language models: insights and future directions
Paper • 2408.12637 • Published • 133
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FAST: Efficient Action Tokenization for Vision-Language-Action Models
Paper • 2501.09747 • Published • 27 -
Tensor Product Attention Is All You Need
Paper • 2501.06425 • Published • 89 -
SPAM: Spike-Aware Adam with Momentum Reset for Stable LLM Training
Paper • 2501.06842 • Published • 16 -
LLaVA-Mini: Efficient Image and Video Large Multimodal Models with One Vision Token
Paper • 2501.03895 • Published • 52
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LLaVA-Mini: Efficient Image and Video Large Multimodal Models with One Vision Token
Paper • 2501.03895 • Published • 52 -
LlamaV-o1: Rethinking Step-by-step Visual Reasoning in LLMs
Paper • 2501.06186 • Published • 65 -
Multimodal LLMs Can Reason about Aesthetics in Zero-Shot
Paper • 2501.09012 • Published • 10
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LLaVA-Mini: Efficient Image and Video Large Multimodal Models with One Vision Token
Paper • 2501.03895 • Published • 52 -
Sa2VA: Marrying SAM2 with LLaVA for Dense Grounded Understanding of Images and Videos
Paper • 2501.04001 • Published • 47 -
Are VLMs Ready for Autonomous Driving? An Empirical Study from the Reliability, Data, and Metric Perspectives
Paper • 2501.04003 • Published • 27 -
VideoRAG: Retrieval-Augmented Generation over Video Corpus
Paper • 2501.05874 • Published • 75
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DocLLM: A layout-aware generative language model for multimodal document understanding
Paper • 2401.00908 • Published • 189 -
COSMO: COntrastive Streamlined MultimOdal Model with Interleaved Pre-Training
Paper • 2401.00849 • Published • 17 -
LLaVA-Plus: Learning to Use Tools for Creating Multimodal Agents
Paper • 2311.05437 • Published • 51 -
LLaVA-Interactive: An All-in-One Demo for Image Chat, Segmentation, Generation and Editing
Paper • 2311.00571 • Published • 43
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Exploring the Potential of Encoder-free Architectures in 3D LMMs
Paper • 2502.09620 • Published • 26 -
The Evolution of Multimodal Model Architectures
Paper • 2405.17927 • Published • 1 -
What matters when building vision-language models?
Paper • 2405.02246 • Published • 103 -
Efficient Architectures for High Resolution Vision-Language Models
Paper • 2501.02584 • Published
-
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
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iVideoGPT: Interactive VideoGPTs are Scalable World Models
Paper • 2405.15223 • Published • 17 -
Meteor: Mamba-based Traversal of Rationale for Large Language and Vision Models
Paper • 2405.15574 • Published • 55 -
An Introduction to Vision-Language Modeling
Paper • 2405.17247 • Published • 90 -
Matryoshka Multimodal Models
Paper • 2405.17430 • Published • 34
-
DocLLM: A layout-aware generative language model for multimodal document understanding
Paper • 2401.00908 • Published • 189 -
COSMO: COntrastive Streamlined MultimOdal Model with Interleaved Pre-Training
Paper • 2401.00849 • Published • 17 -
LLaVA-Plus: Learning to Use Tools for Creating Multimodal Agents
Paper • 2311.05437 • Published • 51 -
LLaVA-Interactive: An All-in-One Demo for Image Chat, Segmentation, Generation and Editing
Paper • 2311.00571 • Published • 43
-
The Evolution of Multimodal Model Architectures
Paper • 2405.17927 • Published • 1 -
What matters when building vision-language models?
Paper • 2405.02246 • Published • 103 -
Efficient Architectures for High Resolution Vision-Language Models
Paper • 2501.02584 • Published -
Building and better understanding vision-language models: insights and future directions
Paper • 2408.12637 • Published • 133
-
Exploring the Potential of Encoder-free Architectures in 3D LMMs
Paper • 2502.09620 • Published • 26 -
The Evolution of Multimodal Model Architectures
Paper • 2405.17927 • Published • 1 -
What matters when building vision-language models?
Paper • 2405.02246 • Published • 103 -
Efficient Architectures for High Resolution Vision-Language Models
Paper • 2501.02584 • Published
-
FAST: Efficient Action Tokenization for Vision-Language-Action Models
Paper • 2501.09747 • Published • 27 -
Tensor Product Attention Is All You Need
Paper • 2501.06425 • Published • 89 -
SPAM: Spike-Aware Adam with Momentum Reset for Stable LLM Training
Paper • 2501.06842 • Published • 16 -
LLaVA-Mini: Efficient Image and Video Large Multimodal Models with One Vision Token
Paper • 2501.03895 • Published • 52
-
LLaVA-Mini: Efficient Image and Video Large Multimodal Models with One Vision Token
Paper • 2501.03895 • Published • 52 -
LlamaV-o1: Rethinking Step-by-step Visual Reasoning in LLMs
Paper • 2501.06186 • Published • 65 -
Multimodal LLMs Can Reason about Aesthetics in Zero-Shot
Paper • 2501.09012 • Published • 10
-
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
-
LLaVA-Mini: Efficient Image and Video Large Multimodal Models with One Vision Token
Paper • 2501.03895 • Published • 52 -
Sa2VA: Marrying SAM2 with LLaVA for Dense Grounded Understanding of Images and Videos
Paper • 2501.04001 • Published • 47 -
Are VLMs Ready for Autonomous Driving? An Empirical Study from the Reliability, Data, and Metric Perspectives
Paper • 2501.04003 • Published • 27 -
VideoRAG: Retrieval-Augmented Generation over Video Corpus
Paper • 2501.05874 • Published • 75