59 citations · 117 across the 12 of their papers we have counts for
13 papers · 1 filter
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-…
Learning Discrete Representations via Constrained Clustering for Effective and Efficient Dense Retrieval
Jingtao Zhan, Jiaxin Mao, Yiqun Liu +3
Dense Retrieval (DR) has achieved state-of-the-art first-stage ranking effectiveness. However, the efficiency of most existing DR models is limited by the large memory cost of stor…
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…
Jointly Optimizing Query Encoder and Product Quantization to Improve Retrieval Performance
Jingtao Zhan, Jiaxin Mao, Yiqun Liu +3
Recently, Information Retrieval community has witnessed fast-paced advances in Dense Retrieval (DR), which performs first-stage retrieval with embedding-based search. Despite the i…
A Large-Scale Rich Context Query and Recommendation Dataset in Online Knowledge-Sharing
Bin Hao, Min Zhang, Weizhi Ma +5
Data plays a vital role in machine learning studies. In the research of recommendation, both user behaviors and side information are helpful to model users. So, large-scale real sc…
Optimizing Dense Retrieval Model Training with Hard Negatives
Jingtao Zhan, Jiaxin Mao, Yiqun Liu +3
Ranking has always been one of the top concerns in information retrieval researches. For decades, the lexical matching signal has dominated the ad-hoc retrieval process, but solely…