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Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 23 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 83 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 146 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25
Collections
Discover the best community collections!
Collections including paper arxiv:2502.02492
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Lightricks/LTX-Video
Image-to-Video • Updated • 332k • 995 -
XLabs-AI/flux-RealismLora
Text-to-Image • Updated • 216k • • 1.04k -
tencent/HunyuanVideo
Text-to-Video • Updated • 7.65k • • 1.68k -
VideoJAM: Joint Appearance-Motion Representations for Enhanced Motion Generation in Video Models
Paper • 2502.02492 • Published • 56
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DynamicScaler: Seamless and Scalable Video Generation for Panoramic Scenes
Paper • 2412.11100 • Published • 7 -
LinGen: Towards High-Resolution Minute-Length Text-to-Video Generation with Linear Computational Complexity
Paper • 2412.09856 • Published • 10 -
DisPose: Disentangling Pose Guidance for Controllable Human Image Animation
Paper • 2412.09349 • Published • 8 -
MEMO: Memory-Guided Diffusion for Expressive Talking Video Generation
Paper • 2412.04448 • Published • 10
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214
Hunyuan3D-1.0
😻Text-to-3D and Image-to-3D Generation
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ROICtrl: Boosting Instance Control for Visual Generation
Paper • 2411.17949 • Published • 82 -
VideoJAM: Joint Appearance-Motion Representations for Enhanced Motion Generation in Video Models
Paper • 2502.02492 • Published • 56 -
Phantom: Subject-consistent video generation via cross-modal alignment
Paper • 2502.11079 • Published • 49
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Motion-I2V: Consistent and Controllable Image-to-Video Generation with Explicit Motion Modeling
Paper • 2401.15977 • Published • 38 -
Lumiere: A Space-Time Diffusion Model for Video Generation
Paper • 2401.12945 • Published • 85 -
AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning
Paper • 2307.04725 • Published • 64 -
Boximator: Generating Rich and Controllable Motions for Video Synthesis
Paper • 2402.01566 • Published • 27