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cs.IR2026
Fine-tuning Small Language Models as Efficient Enterprise Search Relevance Labelers
Yue Kang, Zhuoyi Huang, Benji Schussheim +19
In enterprise search, building high-quality datasets at scale remains a central challenge due to the difficulty of acquiring labeled data. To resolve this challenge, we propose an…
cs.IR2025
EAGER-LLM: Enhancing Large Language Models as Recommenders through Exogenous Behavior-Semantic Integration
Minjie Hong, Yan Xia, Zehan Wang +8
Large language models (LLMs) are increasingly leveraged as foundational backbones in the development of advanced recommender systems, offering enhanced capabilities through their e…