-
Animate-X: Universal Character Image Animation with Enhanced Motion Representation
Paper • 2410.10306 • Published • 53 -
ReCapture: Generative Video Camera Controls for User-Provided Videos using Masked Video Fine-Tuning
Paper • 2411.05003 • Published • 70 -
TIP-I2V: A Million-Scale Real Text and Image Prompt Dataset for Image-to-Video Generation
Paper • 2411.04709 • Published • 25 -
IterComp: Iterative Composition-Aware Feedback Learning from Model Gallery for Text-to-Image Generation
Paper • 2410.07171 • Published • 41
Collections
Discover the best community collections!
Collections including paper arxiv:2412.08580
-
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 • 39 -
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 20
-
Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 21 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 82 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 144 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25
-
CompCap: Improving Multimodal Large Language Models with Composite Captions
Paper • 2412.05243 • Published • 17 -
GraPE: A Generate-Plan-Edit Framework for Compositional T2I Synthesis
Paper • 2412.06089 • Published • 4 -
SILMM: Self-Improving Large Multimodal Models for Compositional Text-to-Image Generation
Paper • 2412.05818 • Published -
FLAIR: VLM with Fine-grained Language-informed Image Representations
Paper • 2412.03561 • Published • 1
-
MS MARCO Web Search: a Large-scale Information-rich Web Dataset with Millions of Real Click Labels
Paper • 2405.07526 • Published • 18 -
Automatic Data Curation for Self-Supervised Learning: A Clustering-Based Approach
Paper • 2405.15613 • Published • 13 -
A Touch, Vision, and Language Dataset for Multimodal Alignment
Paper • 2402.13232 • Published • 13 -
How Do Large Language Models Acquire Factual Knowledge During Pretraining?
Paper • 2406.11813 • Published • 30