4 citations · 9 across the 6 of their papers we have counts for
6 papers
Self-Supervised Interest Transfer Network via Prototypical Contrastive Learning for Recommendation
Guoqiang Sun, Yibin Shen, Sijin Zhou +6
Cross-domain recommendation has attracted increasing attention from industry and academia recently. However, most existing methods do not exploit the interest invariance between do…
Domain-Adaptive Text Classification with Structured Knowledge from Unlabeled Data
Tian Li, Xiang Chen, Zhen Dong +4
Domain adaptive text classification is a challenging problem for the large-scale pretrained language models because they often require expensive additional labeled data to adapt to…
A Simple Information-Based Approach to Unsupervised Domain-Adaptive Aspect-Based Sentiment Analysis
Xiang Chen, Xiaojun Wan
Aspect-based sentiment analysis (ABSA) is a fine-grained sentiment analysis task which aims to extract the aspects from sentences and identify their corresponding sentiments. Aspec…
Cross-Domain Sentiment Classification with In-Domain Contrastive Learning
Tian Li, Xiang Chen, Shanghang Zhang +2
Contrastive learning (CL) has been successful as a powerful representation learning method. In this paper, we propose a contrastive learning framework for cross-domain sentiment cl…
Cross-Domain Sentiment Classification with Contrastive Learning and Mutual Information Maximization
Tian Li, Xiang Chen, Shanghang Zhang +2
Contrastive learning (CL) has been successful as a powerful representation learning method. In this work we propose CLIM: Contrastive Learning with mutual Information Maximization,…
Generative Feature Replay with Orthogonal Weight Modification for Continual Learning
Gehui Shen, Song Zhang, Xiang Chen +1
The ability of intelligent agents to learn and remember multiple tasks sequentially is crucial to achieving artificial general intelligence. Many continual learning (CL) methods ha…