74 citations · 186 across the 49 of their papers we have counts for
7 papers · 1 filter
Low-redundancy Distillation for Continual Learning
RuiQi Liu, Boyu Diao, Libo Huang +4
Continual learning (CL) aims to learn new tasks without erasing previous knowledge. However, current CL methods primarily emphasize improving accuracy while often neglecting traini…
CLIP-KD: An Empirical Study of CLIP Model Distillation
Chuanguang Yang, Zhulin An, Libo Huang +5
Contrastive Language-Image Pre-training (CLIP) has become a promising language-supervised visual pre-training framework. This paper aims to distill small CLIP models supervised by…
Categories of Response-Based, Feature-Based, and Relation-Based Knowledge Distillation
Chuanguang Yang, Xinqiang Yu, Zhulin An +1
Deep neural networks have achieved remarkable performance for artificial intelligence tasks. The success behind intelligent systems often relies on large-scale models with high com…
Modeling Dual Period-Varying Preferences for Takeaway Recommendation
Yuting Zhang, Yiqing Wu, Ran Le +7
Takeaway recommender systems, which aim to accurately provide stores that offer foods meeting users' interests, have served billions of users in our daily life. Different from trad…
Team AcieLee: Technical Report for EPIC-SOUNDS Audio-Based Interaction Recognition Challenge 2023
Yuqi Li, Yizhi Luo, Xiaoshuai Hao +4
In this report, we describe the technical details of our submission to the EPIC-SOUNDS Audio-Based Interaction Recognition Challenge 2023, by Team "AcieLee" (username: Yuqi\_Li). T…
eTag: Class-Incremental Learning with Embedding Distillation and Task-Oriented Generation
Libo Huang, Yan Zeng, Chuanguang Yang +3
Class-Incremental Learning (CIL) aims to solve the neural networks' catastrophic forgetting problem, which refers to the fact that once the network updates on a new task, its perfo…
A Survey on Causal Inference for Recommendation
Huishi Luo, Fuzhen Zhuang, Ruobing Xie +4
Causal inference has recently garnered significant interest among recommender system (RS) researchers due to its ability to dissect cause-and-effect relationships and its broad app…