193 citations · 501 across the 18 of their papers we have counts for
18 papers
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…
Ensemble Ranking Model with Multiple Pretraining Strategies for Web Search
Xiaojie Sun, Lulu Yu, Yiting Wang +2
An effective ranking model usually requires a large amount of training data to learn the relevance between documents and queries. User clicks are often used as training data since…
Feature-Enhanced Network with Hybrid Debiasing Strategies for Unbiased Learning to Rank
Lulu Yu, Yiting Wang, Xiaojie Sun +2
Unbiased learning to rank (ULTR) aims to mitigate various biases existing in user clicks, such as position bias, trust bias, presentation bias, and learn an effective ranker. In th…
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…