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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
Collections
Discover the best community collections!
Collections including paper arxiv:2408.12637
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OpenResearcher: Unleashing AI for Accelerated Scientific Research
Paper • 2408.06941 • Published • 31 -
ControlNeXt: Powerful and Efficient Control for Image and Video Generation
Paper • 2408.06070 • Published • 53 -
Generative Photomontage
Paper • 2408.07116 • Published • 20 -
Building and better understanding vision-language models: insights and future directions
Paper • 2408.12637 • Published • 124
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What matters when building vision-language models?
Paper • 2405.02246 • Published • 101 -
An Introduction to Vision-Language Modeling
Paper • 2405.17247 • Published • 87 -
InternLM-XComposer-2.5: A Versatile Large Vision Language Model Supporting Long-Contextual Input and Output
Paper • 2407.03320 • Published • 93 -
Building and better understanding vision-language models: insights and future directions
Paper • 2408.12637 • Published • 124
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MUMU: Bootstrapping Multimodal Image Generation from Text-to-Image Data
Paper • 2406.18790 • Published • 33 -
OmniGen: Unified Image Generation
Paper • 2409.11340 • Published • 109 -
Show-o: One Single Transformer to Unify Multimodal Understanding and Generation
Paper • 2408.12528 • Published • 51 -
MonoFormer/MonoFormer_ImageNet_256
Updated • 1 • 4
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Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs
Paper • 2406.16860 • Published • 59 -
Understanding Alignment in Multimodal LLMs: A Comprehensive Study
Paper • 2407.02477 • Published • 21 -
LongVILA: Scaling Long-Context Visual Language Models for Long Videos
Paper • 2408.10188 • Published • 51 -
Building and better understanding vision-language models: insights and future directions
Paper • 2408.12637 • Published • 124
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Multimodal Pathway: Improve Transformers with Irrelevant Data from Other Modalities
Paper • 2401.14405 • Published • 12 -
CharXiv: Charting Gaps in Realistic Chart Understanding in Multimodal LLMs
Paper • 2406.18521 • Published • 29 -
xGen-VideoSyn-1: High-fidelity Text-to-Video Synthesis with Compressed Representations
Paper • 2408.12590 • Published • 35 -
Law of Vision Representation in MLLMs
Paper • 2408.16357 • Published • 92
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RLHF Workflow: From Reward Modeling to Online RLHF
Paper • 2405.07863 • Published • 66 -
Chameleon: Mixed-Modal Early-Fusion Foundation Models
Paper • 2405.09818 • Published • 127 -
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
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MotionLLM: Understanding Human Behaviors from Human Motions and Videos
Paper • 2405.20340 • Published • 20 -
Spectrally Pruned Gaussian Fields with Neural Compensation
Paper • 2405.00676 • Published • 8 -
Paint by Inpaint: Learning to Add Image Objects by Removing Them First
Paper • 2404.18212 • Published • 27 -
LoRA Land: 310 Fine-tuned LLMs that Rival GPT-4, A Technical Report
Paper • 2405.00732 • Published • 119
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Chameleon: Mixed-Modal Early-Fusion Foundation Models
Paper • 2405.09818 • Published • 127 -
Matryoshka Multimodal Models
Paper • 2405.17430 • Published • 31 -
Seed-TTS: A Family of High-Quality Versatile Speech Generation Models
Paper • 2406.02430 • Published • 31 -
An Image is Worth 32 Tokens for Reconstruction and Generation
Paper • 2406.07550 • Published • 57