1 citations · 1 across the 6 of their papers we have counts for
6 papers
LIVEditor-14B: Lightning Unified Video Editing via In-Context Sparse Attention
Shitong Shao, Zikai Zhou, Haopeng Li +4
Video editing has evolved toward In-Context Learning (ICL) paradigms, yet the resulting quadratic attention costs create a critical computational bottleneck. In this work, we propo…
Exploring Data-Free LoRA Transferability for Video Diffusion Models
Yuchen Wang, Wenliang Zhong, Lichen Bai +6
Video diffusion models leveraging step distillation or causal distillation have achieved remarkable performance. However, adapting existing LoRAs to these variants remains a critic…
Optimizing Few-Step Generation with Adaptive Matching Distillation
Lichen Bai, Zikai Zhou, Shitong Shao +5
Distribution Matching Distillation (DMD) is a powerful acceleration paradigm, yet its stability is often compromised in Forbidden Zone, regions where the real teacher provides unre…
M^2VAE: Multi-Modal Multi-View Variational Autoencoder for Cold-start Item Recommendation
Chuan He, Yongchao Liu, Qiang Li +3
Cold-start item recommendation is a significant challenge in recommendation systems, particularly when new items are introduced without any historical interaction data. While exist…
Identify Then Recommend: Towards Unsupervised Group Recommendation
Yue Liu, Shihao Zhu, Tianyuan Yang +2
Group Recommendation (GR), which aims to recommend items to groups of users, has become a promising and practical direction for recommendation systems. This paper points out two is…
End-to-end Learnable Clustering for Intent Learning in Recommendation
Yue Liu, Shihao Zhu, Jun Xia +6
Intent learning, which aims to learn users' intents for user understanding and item recommendation, has become a hot research spot in recent years. However, existing methods suffer…