3 papers
cs.IR2026
Deep Research for Recommender Systems
Kesha Ou, Chenghao Wu, Xiaolei Wang +6
The technical foundations of recommender systems have progressed from collaborative filtering to complex neural models and, more recently, large language models. Despite these tech…
cs.IR2025
Addressing Personalized Bias for Unbiased Learning to Rank
Zechun Niu, Lang Mei, Liu Yang +4
Unbiased learning to rank (ULTR), which aims to learn unbiased ranking models from biased user behavior logs, plays an important role in Web search. Previous research on ULTR has s…
cs.IR2025
How do Large Language Models Understand Relevance? A Mechanistic Interpretability Perspective
Qi Liu, Jiaxin Mao, Ji-Rong Wen
Recent studies have shown that large language models (LLMs) can assess relevance and support information retrieval (IR) tasks such as document ranking and relevance judgment genera…