2 citations · 2 across the 3 of their papers we have counts for
5 papers
A Reason-then-Describe Instruction Interpreter for Controllable Video Generation
Shengqiong Wu, Weicai Ye, Yuanxing Zhang +7
Diffusion Transformers have significantly improved video fidelity and temporal coherence, however, practical controllability remains limited. Concise, ambiguous, and compositionall…
Imbalance in Balance: Online Concept Balancing in Generation Models
Yukai Shi, Jiarong Ou, Rui Chen +6
In visual generation tasks, the responses and combinations of complex concepts often lack stability and are error-prone, which remains an under-explored area. In this paper, we att…
Any2Caption:Interpreting Any Condition to Caption for Controllable Video Generation
Shengqiong Wu, Weicai Ye, Jiahao Wang +8
To address the bottleneck of accurate user intent interpretation within the current video generation community, we present Any2Caption, a novel framework for controllable video gen…
Towards Precise Scaling Laws for Video Diffusion Transformers
Yuanyang Yin, Yaqi Zhao, Mingwu Zheng +11
Achieving optimal performance of video diffusion transformers within given data and compute budget is crucial due to their high training costs. This necessitates precisely determin…
DMQR-RAG: Diverse Multi-Query Rewriting for RAG
Zhicong Li, Jiahao Wang, Zhishu Jiang +7
Large language models often encounter challenges with static knowledge and hallucinations, which undermine their reliability. Retrieval-augmented generation (RAG) mitigates these i…