359 citations · 820 across the 131 of their papers we have counts for
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cs.IR2020
Learning To Retrieve: How to Train a Dense Retrieval Model Effectively and Efficiently
Jingtao Zhan, Jiaxin Mao, Yiqun Liu +2
Ranking has always been one of the top concerns in information retrieval research. For decades, lexical matching signal has dominated the ad-hoc retrieval process, but it also has…
cs.IR2020
An Empirical Study of Clarifying Question-Based Systems
Jie Zou, Evangelos Kanoulas, Yiqun Liu
Search and recommender systems that take the initiative to ask clarifying questions to better understand users' information needs are receiving increasing attention from the resear…
cs.IR2020★ 59 cited
RepBERT: Contextualized Text Embeddings for First-Stage Retrieval
Jingtao Zhan, Jiaxin Mao, Yiqun Liu +2
Although exact term match between queries and documents is the dominant method to perform first-stage retrieval, we propose a different approach, called RepBERT, to represent docum…