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20242026
most citedEnhancing Low-Cost Video Editing with Lightweight Adaptors and Temporal-Aware Inversion

2 citations · 3 across the 7 of their papers we have counts for

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cs.CV2026

VideoGen-Agent: Reinforcing Video Generation Agents

Binxu Li, Haoyi Duan, Yuhui Zhang +9

Recent advances in video generative models have enabled high-fidelity, temporally coherent video generation. However, these models often struggle to satisfy prompts requiring speci…

cs.CV2025

Closing the Modality Gap for Mixed Modality Search

Binxu Li, Yuhui Zhang, Xiaohan Wang +3

Mixed modality search -- retrieving information across a heterogeneous corpus composed of images, texts, and multimodal documents -- is an important yet underexplored real-world ap…

cs.CV2025

Divergence Minimization Preference Optimization for Diffusion Model Alignment

Binxu Li, Minkai Xu, Jiaqi Han +2

Diffusion models have achieved remarkable success in generating realistic and versatile images from text prompts. Inspired by the recent advancements of language models, there is a…

cs.CV2025

Efficient Temporal Consistency in Diffusion-Based Video Editing with Adaptor Modules: A Theoretical Framework

Xinyuan Song, Yangfan He, Sida Li +10

Adapter-based methods are commonly used to enhance model performance with minimal additional complexity, especially in video editing tasks that require frame-to-frame consistency.…

cs.CV2025★ 2 cited

Enhancing Low-Cost Video Editing with Lightweight Adaptors and Temporal-Aware Inversion

Yangfan He, Sida Li, Jianhui Wang +11

Recent advancements in text-to-image (T2I) generation using diffusion models have enabled cost-effective video-editing applications by leveraging pre-trained models, eliminating th…