855 citations · 1.4k across the 16 of their papers we have counts for
26 papers
Guided Transformer: Leveraging Multiple External Sources for Representation Learning in Conversational Search
Helia Hashemi, Hamed Zamani, W. Bruce Croft
Asking clarifying questions in response to ambiguous or faceted queries has been recognized as a useful technique for various information retrieval systems, especially conversation…
Open-Retrieval Conversational Question Answering
Chen Qu, Liu Yang, Cen Chen +3
Conversational search is one of the ultimate goals of information retrieval. Recent research approaches conversational search by simplified settings of response ranking and convers…
A Transformer-based Embedding Model for Personalized Product Search
Keping Bi, Qingyao Ai, W. Bruce Croft
Product search is an important way for people to browse and purchase items on E-commerce platforms. While customers tend to make choices based on their personal tastes and preferen…
IART: Intent-aware Response Ranking with Transformers in Information-seeking Conversation Systems
Liu Yang, Minghui Qiu, Chen Qu +5
Personal assistant systems, such as Apple Siri, Google Assistant, Amazon Alexa, and Microsoft Cortana, are becoming ever more widely used. Understanding user intent such as clarifi…
Explainable Product Search with a Dynamic Relation Embedding Model
Qingyao Ai, Yongfeng Zhang, Keping Bi +1
Product search is one of the most popular methods for customers to discover products online. Most existing studies on product search focus on developing effective retrieval models…
Conversational Product Search Based on Negative Feedback
Keping Bi, Qingyao Ai, Yongfeng Zhang +1
Intelligent assistants change the way people interact with computers and make it possible for people to search for products through conversations when they have purchase needs. Dur…