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Collections including paper arxiv:2408.12637

MotionLLM: Understanding Human Behaviors from Human Motions and Videos

Paper • 2405.20340 • Published May 30, 2024 • 20
Spectrally Pruned Gaussian Fields with Neural Compensation

Paper • 2405.00676 • Published May 1, 2024 • 10
Paint by Inpaint: Learning to Add Image Objects by Removing Them First

Paper • 2404.18212 • Published Apr 28, 2024 • 29
LoRA Land: 310 Fine-tuned LLMs that Rival GPT-4, A Technical Report

Paper • 2405.00732 • Published Apr 29, 2024 • 122

Memory Augmented Language Models through Mixture of Word Experts

Paper • 2311.10768 • Published Nov 15, 2023 • 19
System 2 Attention (is something you might need too)

Paper • 2311.11829 • Published Nov 20, 2023 • 43
Fine-tuning Language Models for Factuality

Paper • 2311.08401 • Published Nov 14, 2023 • 30
Orca 2: Teaching Small Language Models How to Reason

Paper • 2311.11045 • Published Nov 18, 2023 • 77

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, 2025
Building and better understanding vision-language models: insights and future directions

Paper • 2408.12637 • Published Aug 22, 2024 • 133

A Single Transformer for Scalable Vision-Language Modeling

Paper • 2407.06438 • Published Jul 8, 2024 • 1
Building and better understanding vision-language models: insights and future directions

Paper • 2408.12637 • Published Aug 22, 2024 • 133
A Survey of Context Engineering for Large Language Models

Paper • 2507.13334 • Published Jul 17, 2025 • 259
MemOS: A Memory OS for AI System

Paper • 2507.03724 • Published Jul 4, 2025 • 157

Learn: Vision Language Models

What matters when building vision-language models?

Paper • 2405.02246 • Published May 3, 2024 • 103
Building and better understanding vision-language models: insights and future directions

Paper • 2408.12637 • Published Aug 22, 2024 • 133

EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters

Paper • 2402.04252 • Published Feb 6, 2024 • 29
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models

Paper • 2402.03749 • Published Feb 6, 2024 • 14
ScreenAI: A Vision-Language Model for UI and Infographics Understanding

Paper • 2402.04615 • Published Feb 7, 2024 • 44
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss

Paper • 2402.05008 • Published Feb 7, 2024 • 23

Locality-aware Parallel Decoding for Efficient Autoregressive Image Generation

Paper • 2507.01957 • Published Jul 2, 2025 • 21
LongVie: Multimodal-Guided Controllable Ultra-Long Video Generation

Paper • 2508.03694 • Published Aug 5, 2025 • 51
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, 2025 • 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, 2025

Vision-Language Models

Building and better understanding vision-language models: insights and future directions

Paper • 2408.12637 • Published Aug 22, 2024 • 133

MIT Talk 31/10 Papers

NVLM: Open Frontier-Class Multimodal LLMs

Paper • 2409.11402 • Published Sep 17, 2024 • 74
BRAVE: Broadening the visual encoding of vision-language models

Paper • 2404.07204 • Published Apr 10, 2024 • 19
Mini-Gemini: Mining the Potential of Multi-modality Vision Language Models

Paper • 2403.18814 • Published Mar 27, 2024 • 47
Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Multimodal Models

Paper • 2409.17146 • Published Sep 25, 2024 • 121

MotionLLM: Understanding Human Behaviors from Human Motions and Videos

Paper • 2405.20340 • Published May 30, 2024 • 20
Spectrally Pruned Gaussian Fields with Neural Compensation

Paper • 2405.00676 • Published May 1, 2024 • 10
Paint by Inpaint: Learning to Add Image Objects by Removing Them First

Paper • 2404.18212 • Published Apr 28, 2024 • 29
LoRA Land: 310 Fine-tuned LLMs that Rival GPT-4, A Technical Report

Paper • 2405.00732 • Published Apr 29, 2024 • 122

EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters

Paper • 2402.04252 • Published Feb 6, 2024 • 29
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models

Paper • 2402.03749 • Published Feb 6, 2024 • 14
ScreenAI: A Vision-Language Model for UI and Infographics Understanding

Paper • 2402.04615 • Published Feb 7, 2024 • 44
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss

Paper • 2402.05008 • Published Feb 7, 2024 • 23

Memory Augmented Language Models through Mixture of Word Experts

Paper • 2311.10768 • Published Nov 15, 2023 • 19
System 2 Attention (is something you might need too)

Paper • 2311.11829 • Published Nov 20, 2023 • 43
Fine-tuning Language Models for Factuality

Paper • 2311.08401 • Published Nov 14, 2023 • 30
Orca 2: Teaching Small Language Models How to Reason

Paper • 2311.11045 • Published Nov 18, 2023 • 77

Locality-aware Parallel Decoding for Efficient Autoregressive Image Generation

Paper • 2507.01957 • Published Jul 2, 2025 • 21
LongVie: Multimodal-Guided Controllable Ultra-Long Video Generation

Paper • 2508.03694 • Published Aug 5, 2025 • 51
Building and better understanding vision-language models: insights and future directions

Paper • 2408.12637 • Published Aug 22, 2024 • 133

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, 2025
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, 2025 • 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, 2025

A Single Transformer for Scalable Vision-Language Modeling

Paper • 2407.06438 • Published Jul 8, 2024 • 1
Building and better understanding vision-language models: insights and future directions

Paper • 2408.12637 • Published Aug 22, 2024 • 133
A Survey of Context Engineering for Large Language Models

Paper • 2507.13334 • Published Jul 17, 2025 • 259
MemOS: A Memory OS for AI System

Paper • 2507.03724 • Published Jul 4, 2025 • 157

Vision-Language Models

Building and better understanding vision-language models: insights and future directions

Paper • 2408.12637 • Published Aug 22, 2024 • 133

Learn: Vision Language Models

What matters when building vision-language models?

Paper • 2405.02246 • Published May 3, 2024 • 103
Building and better understanding vision-language models: insights and future directions

Paper • 2408.12637 • Published Aug 22, 2024 • 133

MIT Talk 31/10 Papers

NVLM: Open Frontier-Class Multimodal LLMs

Paper • 2409.11402 • Published Sep 17, 2024 • 74
BRAVE: Broadening the visual encoding of vision-language models

Paper • 2404.07204 • Published Apr 10, 2024 • 19
Mini-Gemini: Mining the Potential of Multi-modality Vision Language Models

Paper • 2403.18814 • Published Mar 27, 2024 • 47
Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Multimodal Models

Paper • 2409.17146 • Published Sep 25, 2024 • 121

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