4 citations · 10 across the 7 of their papers we have counts for
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cs.IR2024★ 3 cited
Boosting LLM-based Relevance Modeling with Distribution-Aware Robust Learning
Hong Liu, Saisai Gong, Yixin Ji +3
With the rapid advancement of pre-trained large language models (LLMs), recent endeavors have leveraged the capabilities of LLMs in relevance modeling, resulting in enhanced perfor…
cs.AI2024★ 2 cited
CPRM: A LLM-based Continual Pre-training Framework for Relevance Modeling in Commercial Search
Kaixin Wu, Yixin Ji, Zeyuan Chen +9
Relevance modeling between queries and items stands as a pivotal component in commercial search engines, directly affecting the user experience. Given the remarkable achievements o…
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…