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Collections including paper arxiv:2405.17430

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

Paper • 2402.04252 • Published Feb 6 • 25
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models

Paper • 2402.03749 • Published Feb 6 • 12
ScreenAI: A Vision-Language Model for UI and Infographics Understanding

Paper • 2402.04615 • Published Feb 7 • 38
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss

Paper • 2402.05008 • Published Feb 7 • 19

LongVILA: Scaling Long-Context Visual Language Models for Long Videos

Paper • 2408.10188 • Published Aug 19 • 51
xGen-MM (BLIP-3): A Family of Open Large Multimodal Models

Paper • 2408.08872 • Published Aug 16 • 97
Building and better understanding vision-language models: insights and future directions

Paper • 2408.12637 • Published Aug 22 • 115
Show-o: One Single Transformer to Unify Multimodal Understanding and Generation

Paper • 2408.12528 • Published Aug 22 • 50

Matryoshka Multimodal Models

mucai/llava-v1.5-7b-m3

Text Generation • Updated Jun 3 • 705
mucai/llava-next-vicuna-7b-m3

Text Generation • Updated Jun 3 • 177
Matryoshka Multimodal Models

Paper • 2405.17430 • Published May 27 • 30

Matryoshka Multimodal Models

Paper • 2405.17430 • Published May 27 • 30
nyunai/nyun-c2-llama3-56B

Text Generation • Updated Jun 14 • 4.11k • 10

iVideoGPT: Interactive VideoGPTs are Scalable World Models

Paper • 2405.15223 • Published May 24 • 12
Meteor: Mamba-based Traversal of Rationale for Large Language and Vision Models

Paper • 2405.15574 • Published May 24 • 53
An Introduction to Vision-Language Modeling

Paper • 2405.17247 • Published May 27 • 85
Matryoshka Multimodal Models

Paper • 2405.17430 • Published May 27 • 30

Chameleon: Mixed-Modal Early-Fusion Foundation Models

Paper • 2405.09818 • Published May 16 • 125
Matryoshka Multimodal Models

Paper • 2405.17430 • Published May 27 • 30
Seed-TTS: A Family of High-Quality Versatile Speech Generation Models

Paper • 2406.02430 • Published Jun 4 • 29
An Image is Worth 32 Tokens for Reconstruction and Generation

Paper • 2406.07550 • Published Jun 11 • 55

MobileCLIP: Fast Image-Text Models through Multi-Modal Reinforced Training

Paper • 2311.17049 • Published Nov 28, 2023
DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model

Paper • 2405.04434 • Published May 7 • 13
A Study of Autoregressive Decoders for Multi-Tasking in Computer Vision

Paper • 2303.17376 • Published Mar 30, 2023
Sigmoid Loss for Language Image Pre-Training

Paper • 2303.15343 • Published Mar 27, 2023 • 4

image-video llm

Reka Core, Flash, and Edge: A Series of Powerful Multimodal Language Models

Paper • 2404.12387 • Published Apr 18 • 38
Matryoshka Multimodal Models

Paper • 2405.17430 • Published May 27 • 30

vision foundation modesl

vision foundation models

ViTAR: Vision Transformer with Any Resolution

Paper • 2403.18361 • Published Mar 27 • 52
BRAVE: Broadening the visual encoding of vision-language models

Paper • 2404.07204 • Published Apr 10 • 18
CatLIP: CLIP-level Visual Recognition Accuracy with 2.7x Faster Pre-training on Web-scale Image-Text Data

Paper • 2404.15653 • Published Apr 24 • 26
Chameleon: Mixed-Modal Early-Fusion Foundation Models

Paper • 2405.09818 • Published May 16 • 125

DocLLM: A layout-aware generative language model for multimodal document understanding

Paper • 2401.00908 • Published Dec 31, 2023 • 180
COSMO: COntrastive Streamlined MultimOdal Model with Interleaved Pre-Training

Paper • 2401.00849 • Published Jan 1 • 14
LLaVA-Plus: Learning to Use Tools for Creating Multimodal Agents

Paper • 2311.05437 • Published Nov 9, 2023 • 45
LLaVA-Interactive: An All-in-One Demo for Image Chat, Segmentation, Generation and Editing

Paper • 2311.00571 • Published Nov 1, 2023 • 40

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