22 citations · 42 across the 10 of their papers we have counts for
10 papers
Learning Intrinsic Dimension via Information Bottleneck for Explainable Aspect-based Sentiment Analysis
Zhenxiao Cheng, Jie Zhou, Wen Wu +2
Gradient-based explanation methods are increasingly used to interpret neural models in natural language processing (NLP) due to their high fidelity. Such methods determine word-lev…
Metacognition-Enhanced Few-Shot Prompting With Positive Reinforcement
Yu Ji, Wen Wu, Yi Hu +2
Few-shot prompting elicits the remarkable abilities of large language models by equipping them with a few demonstration examples in the input. However, the traditional method of pr…
Is ChatGPT a Good Personality Recognizer? A Preliminary Study
Yu Ji, Wen Wu, Hong Zheng +3
In recent years, personality has been regarded as a valuable personal factor being incorporated into numerous tasks such as sentiment analysis and product recommendation. This has…
A Positive-Unlabeled Metric Learning Framework for Document-Level Relation Extraction with Incomplete Labeling
Ye Wang, Huazheng Pan, Tao Zhang +2
The goal of document-level relation extraction (RE) is to identify relations between entities that span multiple sentences. Recently, incomplete labeling in document-level RE has r…
A Personality-Guided Preference Aggregator for Ephemeral Group Recommendation
Guangze Ye, Wen Wu, Liye Shi +3
Ephemeral group recommendation (EGR) aims to suggest items for a group of users who come together for the first time. Existing work typically consider individual preferences as the…
Tell Model Where to Attend: Improving Interpretability of Aspect-Based Sentiment Classification via Small Explanation Annotations
Zhenxiao Cheng, Jie Zhou, Wen Wu +2
Gradient-based explanation methods play an important role in the field of interpreting complex deep neural networks for NLP models. However, the existing work has shown that the gr…
Self-Attentive Sequential Recommendation with Cheap Causal Convolutions
Jiayi Chen, Wen Wu, Liye Shi +5
Sequential Recommendation is a prominent topic in current research, which uses user behavior sequence as an input to predict future behavior. By assessing the correlation strength…
Multi-channel Attentive Graph Convolutional Network With Sentiment Fusion For Multimodal Sentiment Analysis
Luwei Xiao, Xingjiao Wu, Wen Wu +2
Nowadays, with the explosive growth of multimodal reviews on social media platforms, multimodal sentiment analysis has recently gained popularity because of its high relevance to t…
Long-Tail Session-based Recommendation from Calibration
Jiayi Chen, Wen Wu, Wei Zheng +1
Accurate predictions in session-based recommendations have progressed, but a few studies have focused on skewed recommendation lists caused by popularity bias. Existing models for…
Pyramid Focusing Network for mutation prediction and classification in CT images
Xukun Zhang, Wenxin Hu, Wen Wu
Predicting the mutation status of genes in tumors is of great clinical significance. Recent studies have suggested that certain mutations may be noninvasively predicted by studying…