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cs.IR2024
Towards Boosting LLMs-driven Relevance Modeling with Progressive Retrieved Behavior-augmented Prompting
Zeyuan Chen, Haiyan Wu, Kaixin Wu +5
Relevance modeling is a critical component for enhancing user experience in search engines, with the primary objective of identifying items that align with users' queries. Traditio…
cs.IR2023
Beyond Semantics: Learning a Behavior Augmented Relevance Model with Self-supervised Learning
Zeyuan Chen, Wei Chen, Jia Xu +2
Relevance modeling aims to locate desirable items for corresponding queries, which is crucial for search engines to ensure user experience. Although most conventional approaches ad…