1 citations · 1 across the 4 of their papers we have counts for
4 papers
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…
Q-STRUM Debate: Query-Driven Contrastive Summarization for Recommendation Comparison
George-Kirollos Saad, Scott Sanner
Query-driven recommendation with unknown items poses a challenge for users to understand why certain items are appropriate for their needs. Query-driven Contrastive Summarization (…
Elaborative Subtopic Query Reformulation for Broad and Indirect Queries in Travel Destination Recommendation
Qianfeng Wen, Yifan Liu, Joshua Zhang +4
In Query-driven Travel Recommender Systems (RSs), it is crucial to understand the user intent behind challenging natural language(NL) destination queries such as the broadly worded…
Multi-Aspect Reviewed-Item Retrieval via LLM Query Decomposition and Aspect Fusion
Anton Korikov, George Saad, Ethan Baron +3
While user-generated product reviews often contain large quantities of information, their utility in addressing natural language product queries has been limited, with a key challe…