49 citations · 65 across the 7 of their papers we have counts for
13 papers · 1 filter
L^2R: Lifelong Learning for First-stage Retrieval with Backward-Compatible Representations
Yinqiong Cai, Keping Bi, Yixing Fan +3
First-stage retrieval is a critical task that aims to retrieve relevant document candidates from a large-scale collection. While existing retrieval models have achieved impressive…
Pre-training with Aspect-Content Text Mutual Prediction for Multi-Aspect Dense Retrieval
Xiaojie Sun, Keping Bi, Jiafeng Guo +5
Grounded on pre-trained language models (PLMs), dense retrieval has been studied extensively on plain text. In contrast, there has been little research on retrieving data with mult…
Asking Clarifying Questions Based on Negative Feedback in Conversational Search
Keping Bi, Qingyao Ai, W. Bruce Croft
Users often need to look through multiple search result pages or reformulate queries when they have complex information-seeking needs. Conversational search systems make it possibl…
Leveraging User Behavior History for Personalized Email Search
Keping Bi, Pavel Metrikov, Chunyuan Li +1
An effective email search engine can facilitate users' search tasks and improve their communication efficiency. Users could have varied preferences on various ranking signals of an…
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…
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…