34 citations · 92 across the 30 of their papers we have counts for
4 papers · 1 filter
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…
FinalMLP: An Enhanced Two-Stream MLP Model for CTR Prediction
Kelong Mao, Jieming Zhu, Liangcai Su +3
Click-through rate (CTR) prediction is one of the fundamental tasks for online advertising and recommendation. While multi-layer perceptron (MLP) serves as a core component in many…
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-…