-
iVideoGPT: Interactive VideoGPTs are Scalable World Models
Paper • 2405.15223 • Published • 12 -
Meteor: Mamba-based Traversal of Rationale for Large Language and Vision Models
Paper • 2405.15574 • Published • 53 -
An Introduction to Vision-Language Modeling
Paper • 2405.17247 • Published • 87 -
Matryoshka Multimodal Models
Paper • 2405.17430 • Published • 31
Collections
Discover the best community collections!
Collections including paper arxiv:2408.08872
-
sentence-transformers/all-mpnet-base-v2
Sentence Similarity • Updated • 19.1M • • 946 -
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
Paper • 1910.10683 • Published • 10 -
google-t5/t5-base
Translation • Updated • 1.9M • 654 -
Attention Is All You Need
Paper • 1706.03762 • Published • 50
-
What matters when building vision-language models?
Paper • 2405.02246 • Published • 101 -
MUMU: Bootstrapping Multimodal Image Generation from Text-to-Image Data
Paper • 2406.18790 • Published • 33 -
Building and better understanding vision-language models: insights and future directions
Paper • 2408.12637 • Published • 124 -
Show-o: One Single Transformer to Unify Multimodal Understanding and Generation
Paper • 2408.12528 • Published • 51
-
LongVILA: Scaling Long-Context Visual Language Models for Long Videos
Paper • 2408.10188 • Published • 51 -
xGen-MM (BLIP-3): A Family of Open Large Multimodal Models
Paper • 2408.08872 • Published • 98 -
Building and better understanding vision-language models: insights and future directions
Paper • 2408.12637 • Published • 124 -
Show-o: One Single Transformer to Unify Multimodal Understanding and Generation
Paper • 2408.12528 • Published • 51
-
xGen-MM (BLIP-3): A Family of Open Large Multimodal Models
Paper • 2408.08872 • Published • 98 -
Transfusion: Predict the Next Token and Diffuse Images with One Multi-Modal Model
Paper • 2408.11039 • Published • 58 -
Building and better understanding vision-language models: insights and future directions
Paper • 2408.12637 • Published • 124