Jingtao Zhan

According to our database, Jingtao Zhan authored at least 18 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Capability-aware Prompt Reformulation Learning for Text-to-Image Generation.

Jingtao Zhan, Qingyao Ai, Yiqun Liu, Jia Chen, Shaoping Ma

CoRR, 2024

Scaling Laws For Dense Retrieval.

Yan Fang, Jingtao Zhan, Qingyao Ai, Jiaxin Mao, Weihang Su, Jia Chen, Yiqun Liu

CoRR, 2024

Query Augmentation by Decoding Semantics from Brain Signals.

Ziyi Ye, Jingtao Zhan, Qingyao Ai, Yiqun Liu, Maarten de Rijke, Christina Lioma, Tuukka Ruotsalo

CoRR, 2024

Combining Multiple Supervision for Robust Zero-Shot Dense Retrieval.

Yan Fang, Qingyao Ai, Jingtao Zhan, Yiqun Liu, Xiaolong Wu, Zhao Cao

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Constructing Tree-based Index for Efficient and Effective Dense Retrieval.

Haitao Li, Qingyao Ai, Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Zheng Liu, Zhao Cao

Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

Learning Discrete Representations via Constrained Clustering for Effective and Efficient Dense Retrieval (Extended Abstract).

Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Jiafeng Guo, Min Zhang, Shaoping Ma

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

2022

Disentangled Modeling of Domain and Relevance for Adaptable Dense Retrieval.

Jingtao Zhan, Qingyao Ai, Yiqun Liu, Jiaxin Mao, Xiaohui Xie, Min Zhang, Shaoping Ma

CoRR, 2022

Evaluating Extrapolation Performance of Dense Retrieval.

Jingtao Zhan, Xiaohui Xie, Jiaxin Mao, Yiqun Liu, Min Zhang, Shaoping Ma

CoRR, 2022

Learning Discrete Representations via Constrained Clustering for Effective and Efficient Dense Retrieval.

Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Jiafeng Guo, Min Zhang, Shaoping Ma

Proceedings of the WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21, 2022

Joint Optimization of Multi-vector Representation with Product Quantization.

Yan Fang, Jingtao Zhan, Yiqun Liu, Jiaxin Mao, Min Zhang, Shaoping Ma

Proceedings of the Natural Language Processing and Chinese Computing, 2022

Evaluating Interpolation and Extrapolation Performance of Neural Retrieval Models.

Jingtao Zhan, Xiaohui Xie, Jiaxin Mao, Yiqun Liu, Jiafeng Guo, Min Zhang, Shaoping Ma

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021

Interpreting Dense Retrieval as Mixture of Topics.

Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Jiafeng Guo, Min Zhang, Shaoping Ma

CoRR, 2021

Optimizing Dense Retrieval Model Training with Hard Negatives.

Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Jiafeng Guo, Min Zhang, Shaoping Ma

Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

Jointly Optimizing Query Encoder and Product Quantization to Improve Retrieval Performance.

Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Jiafeng Guo, Min Zhang, Shaoping Ma

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020

Learning To Retrieve: How to Train a Dense Retrieval Model Effectively and Efficiently.

Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Min Zhang, Shaoping Ma

CoRR, 2020

RepBERT: Contextualized Text Embeddings for First-Stage Retrieval.

Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Min Zhang, Shaoping Ma

CoRR, 2020

Leveraging Passage-level Cumulative Gain for Document Ranking.

Zhijing Wu, Jiaxin Mao, Yiqun Liu, Jingtao Zhan, Yukun Zheng, Min Zhang, Shaoping Ma

Proceedings of the WWW '20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020, 2020

An Analysis of BERT in Document Ranking.

Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Min Zhang, Shaoping Ma

Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020