18 citations · 42 across the 13 of their papers we have counts for
13 papers
Improving Legal Case Retrieval with Brain Signals
Ruizhe Zhang, Qingyao Ai, Ziyi Ye +3
The tasks of legal case retrieval have received growing attention from the IR community in the last decade. Relevance feedback techniques with implicit user feedback (e.g., clicks)…
Relevance Feedback with Brain Signals
Ziyi Ye, Xiaohui Xie, Qingyao Ai +4
The Relevance Feedback (RF) process relies on accurate and real-time relevance estimation of feedback documents to improve retrieval performance. Since collecting explicit relevanc…
GNN4EEG: A Benchmark and Toolkit for Electroencephalography Classification with Graph Neural Network
Kaiyuan Zhang, Ziyi Ye, Qingyao Ai +2
Electroencephalography(EEG) classification is a crucial task in neuroscience, neural engineering, and several commercial applications. Traditional EEG classification models, howeve…
T2Ranking: A large-scale Chinese Benchmark for Passage Ranking
Xiaohui Xie, Qian Dong, Bingning Wang +8
Passage ranking involves two stages: passage retrieval and passage re-ranking, which are important and challenging topics for both academics and industries in the area of Informati…
Brain Topography Adaptive Network for Satisfaction Modeling in Interactive Information Access System
Ziyi Ye, Xiaohui Xie, Yiqun Liu +4
With the growth of information on the Web, most users heavily rely on information access systems (e.g., search engines, recommender systems, etc.) in their daily lives. During this…
Disentangled Modeling of Domain and Relevance for Adaptable Dense Retrieval
Jingtao Zhan, Qingyao Ai, Yiqun Liu +4
Recent advance in Dense Retrieval (DR) techniques has significantly improved the effectiveness of first-stage retrieval. Trained with large-scale supervised data, DR models can enc…
Evaluating Interpolation and Extrapolation Performance of Neural Retrieval Models
Jingtao Zhan, Xiaohui Xie, Jiaxin Mao +4
A retrieval model should not only interpolate the training data but also extrapolate well to the queries that are different from the training data. While neural retrieval models ha…
Pre-training Methods in Information Retrieval
Yixing Fan, Xiaohui Xie, Yinqiong Cai +5
The core of information retrieval (IR) is to identify relevant information from large-scale resources and return it as a ranked list to respond to the user's information need. In r…
Web Search via an Efficient and Effective Brain-Machine Interface
Xuesong Chen, Ziyi Ye, Xiaohui Xie +5
While search technologies have evolved to be robust and ubiquitous, the fundamental interaction paradigm has remained relatively stable for decades. With the maturity of the Brain-…
Why Don't You Click: Neural Correlates of Non-Click Behaviors in Web Search
Ziyi Ye, Xiaohui Xie, Yiqun Liu +6
Web search heavily relies on click-through behavior as an essential feedback signal for performance improvement and evaluation. Traditionally, click is usually treated as a positiv…
Towards a Better Understanding Human Reading Comprehension with Brain Signals
Ziyi Ye, Xiaohui Xie, Yiqun Liu +4
Reading comprehension is a complex cognitive process involving many human brain activities. Plenty of works have studied the patterns and attention allocations of reading comprehen…
Constructing an Interaction Behavior Model for Web Image Search
Xiaohui Xie, Jiaxin Mao, Maarten de Rijke +3
User interaction behavior is a valuable source of implicit relevance feedback. In Web image search a different type of search result presentation is used than in general Web search…
Why People Search for Images using Web Search Engines
Xiaohui Xie, Yiqun Liu, Maarten de Rijke +3
What are the intents or goals behind human interactions with image search engines? Knowing why people search for images is of major concern to Web image search engines because user…