200 citations · 1.6k across the 79 of their papers we have counts for
7 papers · 1 filter
One Person, One Model--Learning Compound Router for Sequential Recommendation
Zhiding Liu, Mingyue Cheng, Zhi Li +2
Deep learning has brought significant breakthroughs in sequential recommendation (SR) for capturing dynamic user interests. A series of recent research revealed that models with mo…
Winning the CVPR'2022 AQTC Challenge: A Two-stage Function-centric Approach
Shiwei Wu, Weidong He, Tong Xu +2
Affordance-centric Question-driven Task Completion for Egocentric Assistant(AQTC) is a novel task which helps AI assistant learn from instructional videos and scripts and guide the…
Boosting Factorization Machines via Saliency-Guided Mixup
Chenwang Wu, Defu Lian, Yong Ge +3
Factorization machines (FMs) are widely used in recommender systems due to their adaptability and ability to learn from sparse data. However, for the ubiquitous non-interactive fea…
Cache-Augmented Inbatch Importance Resampling for Training Recommender Retriever
Jin Chen, Defu Lian, Yucheng Li +3
Recommender retrievers aim to rapidly retrieve a fraction of items from the entire item corpus when a user query requests, with the representative two-tower model trained with the…
Graph Adaptive Semantic Transfer for Cross-domain Sentiment Classification
Kai Zhang, Qi Liu, Zhenya Huang +5
Cross-domain sentiment classification (CDSC) aims to use the transferable semantics learned from the source domain to predict the sentiment of reviews in the unlabeled target domai…
Incorporating Dynamic Semantics into Pre-Trained Language Model for Aspect-based Sentiment Analysis
Kai Zhang, Kun Zhang, Mengdi Zhang +4
Aspect-based sentiment analysis (ABSA) predicts sentiment polarity towards a specific aspect in the given sentence. While pre-trained language models such as BERT have achieved gre…
Reinforcement Routing on Proximity Graph for Efficient Recommendation
Chao Feng, Defu Lian, Xiting Wang +3
We focus on Maximum Inner Product Search (MIPS), which is an essential problem in many machine learning communities. Given a query, MIPS finds the most similar items with the maxim…