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Collections including paper arxiv:2501.03895

about 4 hours ago

Depth Anything V2

Paper • 2406.09414 • Published Jun 13, 2024 • 103
An Image is Worth More Than 16x16 Patches: Exploring Transformers on Individual Pixels

Paper • 2406.09415 • Published Jun 13, 2024 • 51
Physics3D: Learning Physical Properties of 3D Gaussians via Video Diffusion

Paper • 2406.04338 • Published Jun 6, 2024 • 39
SAM 2: Segment Anything in Images and Videos

Paper • 2408.00714 • Published Aug 1, 2024 • 119

Exploring the Potential of Encoder-free Architectures in 3D LMMs

Paper • 2502.09620 • Published Feb 13 • 26
The Evolution of Multimodal Model Architectures

Paper • 2405.17927 • Published May 28, 2024 • 1
What matters when building vision-language models?

Paper • 2405.02246 • Published May 3, 2024 • 103
Efficient Architectures for High Resolution Vision-Language Models

Paper • 2501.02584 • Published Jan 5

Multimodal-Models

LLaVA-Mini: Efficient Image and Video Large Multimodal Models with One Vision Token

Paper • 2501.03895 • Published Jan 7 • 52

Image-Video General Tasks

Sa2VA: Marrying SAM2 with LLaVA for Dense Grounded Understanding of Images and Videos

Paper • 2501.04001 • Published Jan 7 • 47
LLaVA-Mini: Efficient Image and Video Large Multimodal Models with One Vision Token

Paper • 2501.03895 • Published Jan 7 • 52
An Empirical Study of Autoregressive Pre-training from Videos

Paper • 2501.05453 • Published Jan 9 • 41
MatchAnything: Universal Cross-Modality Image Matching with Large-Scale Pre-Training

Paper • 2501.07556 • Published Jan 13 • 7

LLaVA-Mini: Efficient Image and Video Large Multimodal Models with One Vision Token

Paper • 2501.03895 • Published Jan 7 • 52
DocLLM: A layout-aware generative language model for multimodal document understanding

Paper • 2401.00908 • Published Dec 31, 2023 • 189

The Evolution of Multimodal Model Architectures

Paper • 2405.17927 • Published May 28, 2024 • 1
What matters when building vision-language models?

Paper • 2405.02246 • Published May 3, 2024 • 103
Efficient Architectures for High Resolution Vision-Language Models

Paper • 2501.02584 • Published Jan 5
Building and better understanding vision-language models: insights and future directions

Paper • 2408.12637 • Published Aug 22, 2024 • 133

ML Optimization Papers

FAST: Efficient Action Tokenization for Vision-Language-Action Models

Paper • 2501.09747 • Published Jan 16 • 27
Tensor Product Attention Is All You Need

Paper • 2501.06425 • Published Jan 11 • 90
SPAM: Spike-Aware Adam with Momentum Reset for Stable LLM Training

Paper • 2501.06842 • Published Jan 12 • 16
LLaVA-Mini: Efficient Image and Video Large Multimodal Models with One Vision Token

Paper • 2501.03895 • Published Jan 7 • 52

Multimodal models

Papers on AI models that combine vision and language capabilities.

LLaVA-Mini: Efficient Image and Video Large Multimodal Models with One Vision Token

Paper • 2501.03895 • Published Jan 7 • 52
LlamaV-o1: Rethinking Step-by-step Visual Reasoning in LLMs

Paper • 2501.06186 • Published Jan 10 • 65
Multimodal LLMs Can Reason about Aesthetics in Zero-Shot

Paper • 2501.09012 • Published Jan 15 • 10

LLaVA-Mini: Efficient Image and Video Large Multimodal Models with One Vision Token

Paper • 2501.03895 • Published Jan 7 • 52
Sa2VA: Marrying SAM2 with LLaVA for Dense Grounded Understanding of Images and Videos

Paper • 2501.04001 • Published Jan 7 • 47
Are VLMs Ready for Autonomous Driving? An Empirical Study from the Reliability, Data, and Metric Perspectives

Paper • 2501.04003 • Published Jan 7 • 27
VideoRAG: Retrieval-Augmented Generation over Video Corpus

Paper • 2501.05874 • Published Jan 10 • 75

2025 LLM Papers on Hugging Face with Japanese Memos

MotionBench: Benchmarking and Improving Fine-grained Video Motion Understanding for Vision Language Models

Paper • 2501.02955 • Published Jan 6 • 44
2.5 Years in Class: A Multimodal Textbook for Vision-Language Pretraining

Paper • 2501.00958 • Published Jan 1 • 107
MMVU: Measuring Expert-Level Multi-Discipline Video Understanding

Paper • 2501.12380 • Published Jan 21 • 85
VideoWorld: Exploring Knowledge Learning from Unlabeled Videos

Paper • 2501.09781 • Published Jan 16 • 28

about 4 hours ago

Depth Anything V2

Paper • 2406.09414 • Published Jun 13, 2024 • 103
An Image is Worth More Than 16x16 Patches: Exploring Transformers on Individual Pixels

Paper • 2406.09415 • Published Jun 13, 2024 • 51
Physics3D: Learning Physical Properties of 3D Gaussians via Video Diffusion

Paper • 2406.04338 • Published Jun 6, 2024 • 39
SAM 2: Segment Anything in Images and Videos

Paper • 2408.00714 • Published Aug 1, 2024 • 119

The Evolution of Multimodal Model Architectures

Paper • 2405.17927 • Published May 28, 2024 • 1
What matters when building vision-language models?

Paper • 2405.02246 • Published May 3, 2024 • 103
Efficient Architectures for High Resolution Vision-Language Models

Paper • 2501.02584 • Published Jan 5
Building and better understanding vision-language models: insights and future directions

Paper • 2408.12637 • Published Aug 22, 2024 • 133

Exploring the Potential of Encoder-free Architectures in 3D LMMs

Paper • 2502.09620 • Published Feb 13 • 26
The Evolution of Multimodal Model Architectures

Paper • 2405.17927 • Published May 28, 2024 • 1
What matters when building vision-language models?

Paper • 2405.02246 • Published May 3, 2024 • 103
Efficient Architectures for High Resolution Vision-Language Models

Paper • 2501.02584 • Published Jan 5

ML Optimization Papers

FAST: Efficient Action Tokenization for Vision-Language-Action Models

Paper • 2501.09747 • Published Jan 16 • 27
Tensor Product Attention Is All You Need

Paper • 2501.06425 • Published Jan 11 • 90
SPAM: Spike-Aware Adam with Momentum Reset for Stable LLM Training

Paper • 2501.06842 • Published Jan 12 • 16
LLaVA-Mini: Efficient Image and Video Large Multimodal Models with One Vision Token

Paper • 2501.03895 • Published Jan 7 • 52

Multimodal-Models

LLaVA-Mini: Efficient Image and Video Large Multimodal Models with One Vision Token

Paper • 2501.03895 • Published Jan 7 • 52

Multimodal models

Papers on AI models that combine vision and language capabilities.

LLaVA-Mini: Efficient Image and Video Large Multimodal Models with One Vision Token

Paper • 2501.03895 • Published Jan 7 • 52
LlamaV-o1: Rethinking Step-by-step Visual Reasoning in LLMs

Paper • 2501.06186 • Published Jan 10 • 65
Multimodal LLMs Can Reason about Aesthetics in Zero-Shot

Paper • 2501.09012 • Published Jan 15 • 10

Image-Video General Tasks

Sa2VA: Marrying SAM2 with LLaVA for Dense Grounded Understanding of Images and Videos

Paper • 2501.04001 • Published Jan 7 • 47
LLaVA-Mini: Efficient Image and Video Large Multimodal Models with One Vision Token

Paper • 2501.03895 • Published Jan 7 • 52
An Empirical Study of Autoregressive Pre-training from Videos

Paper • 2501.05453 • Published Jan 9 • 41
MatchAnything: Universal Cross-Modality Image Matching with Large-Scale Pre-Training

Paper • 2501.07556 • Published Jan 13 • 7

LLaVA-Mini: Efficient Image and Video Large Multimodal Models with One Vision Token

Paper • 2501.03895 • Published Jan 7 • 52
Sa2VA: Marrying SAM2 with LLaVA for Dense Grounded Understanding of Images and Videos

Paper • 2501.04001 • Published Jan 7 • 47
Are VLMs Ready for Autonomous Driving? An Empirical Study from the Reliability, Data, and Metric Perspectives

Paper • 2501.04003 • Published Jan 7 • 27
VideoRAG: Retrieval-Augmented Generation over Video Corpus

Paper • 2501.05874 • Published Jan 10 • 75

LLaVA-Mini: Efficient Image and Video Large Multimodal Models with One Vision Token

Paper • 2501.03895 • Published Jan 7 • 52
DocLLM: A layout-aware generative language model for multimodal document understanding

Paper • 2401.00908 • Published Dec 31, 2023 • 189

2025 LLM Papers on Hugging Face with Japanese Memos

MotionBench: Benchmarking and Improving Fine-grained Video Motion Understanding for Vision Language Models

Paper • 2501.02955 • Published Jan 6 • 44
2.5 Years in Class: A Multimodal Textbook for Vision-Language Pretraining

Paper • 2501.00958 • Published Jan 1 • 107
MMVU: Measuring Expert-Level Multi-Discipline Video Understanding

Paper • 2501.12380 • Published Jan 21 • 85
VideoWorld: Exploring Knowledge Learning from Unlabeled Videos

Paper • 2501.09781 • Published Jan 16 • 28

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