4 papers · 1 filter
Bayesian Active Learning with Gaussian Processes Guided by LLM Relevance Scoring for Dense Passage Retrieval
Junyoung Kim, Anton Korikov, Jiazhou Liang +5
While Large Language Models (LLMs) exhibit exceptional zero-shot relevance modeling, their high computational cost necessitates framing passage retrieval as a budget-constrained gl…
Multimodal Item Scoring for Natural Language Recommendation via Gaussian Process Regression with LLM Relevance Judgments
Yifan Liu, Qianfeng Wen, Jiazhou Liang +6
Natural Language Recommendation (NLRec) generates item suggestions based on the relevance between user-issued NL requests and NL item description passages. Existing NLRec approache…
Empowering Retrieval-based Conversational Recommendation with Contrasting User Preferences
Heejin Kook, Junyoung Kim, Seongmin Park +1
Conversational recommender systems (CRSs) are designed to suggest the target item that the user is likely to prefer through multi-turn conversations. Recent studies stress that cap…
MARS: Matching Attribute-aware Representations for Text-based Sequential Recommendation
Hyunsoo Kim, Junyoung Kim, Minjin Choi +2
Sequential recommendation aims to predict the next item a user is likely to prefer based on their sequential interaction history. Recently, text-based sequential recommendation has…