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EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 25 -
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models
Paper • 2402.03749 • Published • 12 -
ScreenAI: A Vision-Language Model for UI and Infographics Understanding
Paper • 2402.04615 • Published • 38 -
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 19
Collections
Discover the best community collections!
Collections including paper arxiv:2405.02246
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LLaVA-Plus: Learning to Use Tools for Creating Multimodal Agents
Paper • 2311.05437 • Published • 47 -
Visual Instruction Tuning
Paper • 2304.08485 • Published • 13 -
Improved Baselines with Visual Instruction Tuning
Paper • 2310.03744 • Published • 37 -
Making Large Multimodal Models Understand Arbitrary Visual Prompts
Paper • 2312.00784 • Published • 2
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What matters when building vision-language models?
Paper • 2405.02246 • Published • 98 -
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 • 118 -
Show-o: One Single Transformer to Unify Multimodal Understanding and Generation
Paper • 2408.12528 • Published • 50
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What matters when building vision-language models?
Paper • 2405.02246 • Published • 98 -
An Introduction to Vision-Language Modeling
Paper • 2405.17247 • Published • 85 -
InternLM-XComposer-2.5: A Versatile Large Vision Language Model Supporting Long-Contextual Input and Output
Paper • 2407.03320 • Published • 92 -
Building and better understanding vision-language models: insights and future directions
Paper • 2408.12637 • Published • 118
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Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation
Paper • 2406.06525 • Published • 65 -
Husky: A Unified, Open-Source Language Agent for Multi-Step Reasoning
Paper • 2406.06469 • Published • 24 -
Buffer of Thoughts: Thought-Augmented Reasoning with Large Language Models
Paper • 2406.04271 • Published • 28 -
Block Transformer: Global-to-Local Language Modeling for Fast Inference
Paper • 2406.02657 • Published • 37
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What matters when building vision-language models?
Paper • 2405.02246 • Published • 98 -
An Introduction to Vision-Language Modeling
Paper • 2405.17247 • Published • 85 -
DeMamba: AI-Generated Video Detection on Million-Scale GenVideo Benchmark
Paper • 2405.19707 • Published • 5 -
Scaling Up Your Kernels: Large Kernel Design in ConvNets towards Universal Representations
Paper • 2410.08049 • Published • 8
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MobileCLIP: Fast Image-Text Models through Multi-Modal Reinforced Training
Paper • 2311.17049 • Published -
DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model
Paper • 2405.04434 • Published • 13 -
A Study of Autoregressive Decoders for Multi-Tasking in Computer Vision
Paper • 2303.17376 • Published -
Sigmoid Loss for Language Image Pre-Training
Paper • 2303.15343 • Published • 4
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Visual Fact Checker: Enabling High-Fidelity Detailed Caption Generation
Paper • 2404.19752 • Published • 22 -
How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites
Paper • 2404.16821 • Published • 53 -
MoAI: Mixture of All Intelligence for Large Language and Vision Models
Paper • 2403.07508 • Published • 75 -
MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training
Paper • 2403.09611 • Published • 124