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cs.IR2025
A Simple but Effective Elaborative Query Reformulation Approach for Natural Language Recommendation
Qianfeng Wen, Yifan Liu, Justin Cui +4
Natural Language (NL) recommender systems aim to retrieve relevant items from free-form user queries and item descriptions. Existing systems often rely on dense retrieval (DR), whi…
cs.IR2025
Batched Self-Consistency Improves LLM Relevance Assessment and Ranking
Anton Korikov, Pan Du, Scott Sanner +1
LLM query-passage relevance assessment is typically studied using a one-by-one pointwise (PW) strategy where each LLM call judges one passage at a time. However, this strategy requ…