My name is Jingtao Zhan (詹靖涛, in Chinese). I am now a third year PhD student at Department of Computer Science and Technology, Tsinghua University. My supervisors are Prof. Shaoping Ma and Prof. Yiqun Liu.

My research lies in Information Retrieval and Web Search. I currently focus on Dense Retrieval with a wide interest in improving its effectiveness, efficiency, and interpretability.

I also served as a reviewer and PC member for SIGIR, ACL, WSDM, CIKM, and COLING.

News

• 10.2022, I gave an invited talk to Amazon Alexa AI about “Disentangled Modeling of Domain and Relevance for Adaptable Neural Retrieval”. [paper] [code]
• 09.2022, I gave an invited talk to Alibaba (the DAMO NLP team and OpenSearch team) about “Disentangled Modeling of Domain and Relevance for Adaptable Neural Retrieval”. [paper] [code]
• 03.2022, I gave invited talks to BIT, Jina.ai, and Baidu about “Effective and Efficient Dense Retrieval via Joint Optimization with Compact Index”. [paper] [code]
• 02.2022, Our paper “Learning Discrete Representations via Constrained Clustering for Effective and Efficient Dense Retrieval” won WSDM’22 Best Paper Award . [paper] [code]
• 01.2022, I gave an invited talk to Glasgow IR Group about “Effective and Efficient Dense Retrieval via Joint Optimization with Compact Index”. [paper] [code]

Publications

• Disentangled Modeling of Domain and Relevance for Adaptable Dense Retrieval.
  Jingtao Zhan, Qingyao Ai, Yiqun Liu, Jiaxin Mao, Xiaohui Xie, Min Zhang, and Shaoping Ma.
  (ArXiv). [paper] [code]

• Evaluating Interpolation and Extrapolation Performance of Neural Retrieval Models.
  Jingtao Zhan, Xiaohui Xie, Jiaxin Mao, Yiqun Liu, Jiafeng Guo, Min Zhang and Shaoping Ma.
  The 31th ACM International Conference on Information and Knowledge Management. (CIKM 2022). [paper] [code]

• Learning Discrete Representations via Constrained Clustering for Effective and Efficient Dense Retrieval.
  Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Jiafeng Guo, Min Zhang and Shaoping Ma.
  The 15th ACM International Conference on Web Search and Data Mining. (WSDM 2022 Best Paper Award). [paper] [code]

• Jointly Optimizing Query Encoder and Product Quantization to Improve Retrieval Performance.
  Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Jiafeng Guo, Min Zhang and Shaoping Ma.
  The 30th ACM International Conference on Information and Knowledge Management. (CIKM 2021). [paper] [code]

• Optimizing Dense Retrieval Model Training with Hard Negatives.
  Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Jiafeng Guo, Min Zhang and Shaoping Ma.
  The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval. (SIGIR 2021). [paper] [code]

• RepBERT: Contextualized Text Embeddings for First-Stage Retrieval.
  Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Min Zhang, and Shaoping Ma.
  (ArXiv). [paper]. [code]

• An Analysis of BERT in Document Ranking.
  Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Min Zhang, and Shaoping Ma.
  The 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval. Short Paper. (SIGIR 2020). [paper] [code]

• Leveraging Passage-level Cumulative Gain for Document Ranking.
  Zhijing Wu, Jiaxin Mao, Yiqun Liu, Jingtao Zhan, Yukun Zheng, Min Zhang and Shaoping Ma.
  The Web Conference 2020. (WWW 2020). [paper]

Education

• 2020-present, Ph.D. student, Computer Science, Tsinghua University.
• 2016-2020, B.E., Electronic Engineering, Tsinghua University.

Honors and Awards

• 2022, Longfor Scholarship
• 2022, Overall Excellence Scholarship (First Prize), Tsinghua University. (Top 5%)
• 2022, WSDM’22 Best Paper Award
• 2021, Overall Excellence Scholarship (Second Prize), Tsinghua University. (Top 10%)
• 2020, Outstanding Graduate of Beijing
• 2020, Outstanding Graduate of Tsinghua University
• 2019, National Encouragement Scholarship
• 2017, National Encouragement Scholarship