1 citations · 1 across the 4 of their papers we have counts for
4 papers
Generalized Pseudo-Relevance Feedback
Yiteng Tu, Weihang Su, Yujia Zhou +4
Query rewriting is a fundamental technique in information retrieval (IR). It typically employs the retrieval result as relevance feedback to refine the query and thereby addresses…
Harnessing Multimodal Large Language Models for Personalized Product Search with Query-aware Refinement
Beibei Zhang, Yanan Lu, Ruobing Xie +4
Personalized product search (PPS) aims to retrieve products relevant to the given query considering user preferences within their purchase histories. Since large language models (L…
Unsupervised dense retrieval with conterfactual contrastive learning
Haitian Chen, Qingyao Ai, Xiao Wang +3
Efficiently retrieving a concise set of candidates from a large document corpus remains a pivotal challenge in Information Retrieval (IR). Neural retrieval models, particularly den…
Reinforcement Learning to Rank Using Coarse-grained Rewards
Yiteng Tu, Zhichao Xu, Tao Yang +6
Learning to rank (LTR) plays a crucial role in various Information Retrieval (IR) tasks. Although supervised LTR methods based on fine-grained relevance labels (e.g., document-leve…