30 citations · 101 across the 45 of their papers we have counts for
5 papers · 1 filter
Collaboration and Transition: Distilling Item Transitions into Multi-Query Self-Attention for Sequential Recommendation
Tianyu Zhu, Yansong Shi, Yuan Zhang +3
Modern recommender systems employ various sequential modules such as self-attention to learn dynamic user interests. However, these methods are less effective in capturing collabor…
MoqaGPT : Zero-Shot Multi-modal Open-domain Question Answering with Large Language Model
Le Zhang, Yihong Wu, Fengran Mo +2
Multi-modal open-domain question answering typically requires evidence retrieval from databases across diverse modalities, such as images, tables, passages, etc. Even Large Languag…
Learning to Relate to Previous Turns in Conversational Search
Fengran Mo, Jian-Yun Nie, Kaiyu Huang +4
Conversational search allows a user to interact with a search system in multiple turns. A query is strongly dependent on the conversation context. An effective way to improve retri…
ConvGQR: Generative Query Reformulation for Conversational Search
Fengran Mo, Kelong Mao, Yutao Zhu +3
In conversational search, the user's real search intent for the current turn is dependent on the previous conversation history. It is challenging to determine a good search query f…
Large Language Models Know Your Contextual Search Intent: A Prompting Framework for Conversational Search
Kelong Mao, Zhicheng Dou, Fengran Mo +3
Precisely understanding users' contextual search intent has been an important challenge for conversational search. As conversational search sessions are much more diverse and long-…