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17 papers · 1 filter
Improving the Shortest Plank: Vulnerability-Aware Adversarial Training for Robust Recommender System
Kaike Zhang, Qi Cao, Yunfan Wu +3
Recommender systems play a pivotal role in mitigating information overload in various fields. Nonetheless, the inherent openness of these systems introduces vulnerabilities, allowi…
Unified Dual-Intent Translation for Joint Modeling of Search and Recommendation
Yuting Zhang, Yiqing Wu, Ruidong Han +7
Recommendation systems, which assist users in discovering their preferred items among numerous options, have served billions of users across various online platforms. Intuitively,…
Popularity Debiasing from Exposure to Interaction in Collaborative Filtering
Yuanhao Liu, Qi Cao, Huawei Shen +3
Recommender systems often suffer from popularity bias, where popular items are overly recommended while sacrificing unpopular items. Existing researches generally focus on ensuring…
User-Centric Conversational Recommendation with Multi-Aspect User Modeling
Shuokai Li, Ruobing Xie, Yongchun Zhu +3
Conversational recommender systems (CRS) aim to provide highquality recommendations in conversations. However, most conventional CRS models mainly focus on the dialogue understandi…
FedMatch: Federated Learning Over Heterogeneous Question Answering Data
Jiangui Chen, Ruqing Zhang, Jiafeng Guo +2
Question Answering (QA), a popular and promising technique for intelligent information access, faces a dilemma about data as most other AI techniques. On one hand, modern QA method…
Jointly Optimizing Query Encoder and Product Quantization to Improve Retrieval Performance
Jingtao Zhan, Jiaxin Mao, Yiqun Liu +3
Recently, Information Retrieval community has witnessed fast-paced advances in Dense Retrieval (DR), which performs first-stage retrieval with embedding-based search. Despite the i…