306 citations · 560 across the 35 of their papers we have counts for
23 papers · 1 filter
Cognitive Biases in Large Language Models for News Recommendation
Yougang Lyu, Xiaoyu Zhang, Zhaochun Ren +1
Despite large language models (LLMs) increasingly becoming important components of news recommender systems, employing LLMs in such systems introduces new risks, such as the influe…
Information Discovery in e-Commerce
Zhaochun Ren, Xiangnan He, Dawei Yin +1
Electronic commerce, or e-commerce, is the buying and selling of goods and services, or the transmitting of funds or data online. E-commerce platforms come in many kinds, with glob…
Learning Robust Sequential Recommenders through Confident Soft Labels
Shiguang Wu, Xin Xin, Pengjie Ren +4
Sequential recommenders that are trained on implicit feedback are usually learned as a multi-class classification task through softmax-based loss functions on one-hot class labels.…
Generalizing Few-Shot Named Entity Recognizers to Unseen Domains with Type-Related Features
Zihan Wang, Ziqi Zhao, Zhumin Chen +3
Few-shot named entity recognition (NER) has shown remarkable progress in identifying entities in low-resource domains. However, few-shot NER methods still struggle with out-of-doma…
Information Retrieval Meets Large Language Models: A Strategic Report from Chinese IR Community
Qingyao Ai, Ting Bai, Zhao Cao +30
The research field of Information Retrieval (IR) has evolved significantly, expanding beyond traditional search to meet diverse user information needs. Recently, Large Language Mod…
Towards Explainable Conversational Recommender Systems
Shuyu Guo, Shuo Zhang, Weiwei Sun +3
Explanations in conventional recommender systems have demonstrated benefits in helping the user understand the rationality of the recommendations and improving the system's efficie…