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Windows Agent Arena: Evaluating Multi-Modal OS Agents at Scale
Paper • 2409.08264 • Published • 44 -
PixWizard: Versatile Image-to-Image Visual Assistant with Open-Language Instructions
Paper • 2409.15278 • Published • 24 -
Agent S: An Open Agentic Framework that Uses Computers Like a Human
Paper • 2410.08164 • Published • 24
Collections
Discover the best community collections!
Collections including paper arxiv:2409.15278
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LinFusion: 1 GPU, 1 Minute, 16K Image
Paper • 2409.02097 • Published • 33 -
Phidias: A Generative Model for Creating 3D Content from Text, Image, and 3D Conditions with Reference-Augmented Diffusion
Paper • 2409.11406 • Published • 26 -
Diffusion Models Are Real-Time Game Engines
Paper • 2408.14837 • Published • 121 -
Segment Anything with Multiple Modalities
Paper • 2408.09085 • Published • 21
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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
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Controllable Text Generation for Large Language Models: A Survey
Paper • 2408.12599 • Published • 64 -
xGen-VideoSyn-1: High-fidelity Text-to-Video Synthesis with Compressed Representations
Paper • 2408.12590 • Published • 35 -
Real-Time Video Generation with Pyramid Attention Broadcast
Paper • 2408.12588 • Published • 16 -
Transfusion: Predict the Next Token and Diffuse Images with One Multi-Modal Model
Paper • 2408.11039 • Published • 58
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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 • 40 -
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 20