5 papers
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…
Transparent Reference-free Automated Evaluation of Open-Ended User Survey Responses
Subin An, Yugyeong Ji, Junyoung Kim +3
Open-ended survey responses provide valuable insights in marketing research, but low-quality responses not only burden researchers with manual filtering but also risk leading to mi…
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…
ConCSE: Unified Contrastive Learning and Augmentation for Code-Switched Embeddings
Jangyeong Jeon, Sangyeon Cho, Minuk Ma +1
This paper examines the Code-Switching (CS) phenomenon where two languages intertwine within a single utterance. There exists a noticeable need for research on the CS between Engli…