1 citations · 1 across the 7 of their papers we have counts for
7 papers
Failure-Informed Image Self-Augmentation for Multimodal Large Language Model Self-Improvement
Chunyang Jiang, Pingping Zhang, Yuzhi Zhao +9
Multimodal large language models (MLLMs) have achieved remarkable performance across vision-language tasks, but their progress depends heavily on large-scale, high-quality multimod…
HOMIE: Human-object Centric Video Personalization via Multimodal Intelligent Enhancement
Yiyang Cai, Nan Chen, Rongchang Xie +8
Human-object centric video personalization (HOCVP) is a core task within subject-driven video generation. However, existing methods suffer from two key limitations. First, most app…
ReBind: Multi-Reference Video Editing via Structured Instructions with Explicit Reference Relationships
Xinyu Liu, Shihao Li, Weihong Lin +10
Recent diffusion-based video generation models have made significant progress in multi-reference image-conditioned video editing. However, existing methods still struggle to coordi…
DomainShuttle: Freeform Open Domain Subject-driven Text-to-video Generation
Nan Chen, Yiyang Cai, Rongchang Xie +7
Open domain subject-driven text-to-video (S2V) generation has drawn significant interest in academia and industry. Open domain S2V mainly involves two scenarios: in-domain, which r…
Semantic Voting: A Self-Evaluation-Free Approach for Efficient LLM Self-Improvement on Unverifiable Open-ended Tasks
Chunyang Jiang, Yonggang Zhang, Yiyang Cai +5
The rising cost of acquiring supervised data has driven significant interest in self-improvement for large language models (LLMs). Straightforward unsupervised signals like majorit…
Graceful Forgetting in Generative Language Models
Chunyang Jiang, Chi-min Chan, Yiyang Cai +3
Recently, the pretrain-finetune paradigm has become a cornerstone in various deep learning areas. While in general the pre-trained model would promote both effectiveness and effici…
Foundation Cures Personalization: Improving Personalized Models' Prompt Consistency via Hidden Foundation Knowledge
Yiyang Cai, Zhengkai Jiang, Yulong Liu +4
Facial personalization faces challenges to maintain identity fidelity without disrupting the foundation model's prompt consistency. The mainstream personalization models employ ide…