55 citations · 102 across the 10 of their papers we have counts for
6 papers · 1 filter
Breaking the Top- Barrier: Advancing Top- Ranking Metrics Optimization in Recommender Systems
Weiqin Yang, Jiawei Chen, Shengjia Zhang +5
In the realm of recommender systems (RS), Top- ranking metrics such as NDCG@ are the gold standard for evaluating recommendation performance. However, during the training of…
MSL: Not All Tokens Are What You Need for Tuning LLM as a Recommender
Bohao Wang, Feng Liu, Jiawei Chen +7
Large language models (LLMs), known for their comprehension capabilities and extensive knowledge, have been increasingly applied to recommendation systems (RS). Given the fundament…
Rankformer: A Graph Transformer for Recommendation based on Ranking Objective
Sirui Chen, Shen Han, Jiawei Chen +6
Recommender Systems (RS) aim to generate personalized ranked lists for each user and are evaluated using ranking metrics. Although personalized ranking is a fundamental aspect of R…
Distributionally Robust Graph-based Recommendation System
Bohao Wang, Jiawei Chen, Changdong Li +6
With the capacity to capture high-order collaborative signals, Graph Neural Networks (GNNs) have emerged as powerful methods in Recommender Systems (RS). However, their efficacy of…
CDR: Conservative Doubly Robust Learning for Debiased Recommendation
ZiJie Song, JiaWei Chen, Sheng Zhou +4
In recommendation systems (RS), user behavior data is observational rather than experimental, resulting in widespread bias in the data. Consequently, tackling bias has emerged as a…
Transition Propagation Graph Neural Networks for Temporal Networks
Tongya Zheng, Zunlei Feng, Tianli Zhang +6
Researchers of temporal networks (e.g., social networks and transaction networks) have been interested in mining dynamic patterns of nodes from their diverse interactions. Inspired…