Publications

2026

1. SIGIR

   TEC: A Collection of Human Trial-and-error Trajectories for Problem Solving

   Xinkai Zhang, Jingtao Zhan^*, Yiqun Liu, and Qingyao Ai^*

   In Proceedings of the 49th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2026

   DOI Bib

   @inproceedings{zhang2026tec,
     title = {{TEC}: A Collection of Human Trial-and-error Trajectories for Problem Solving},
     author = {Zhang, Xinkai and Zhan, Jingtao and Liu, Yiqun and Ai, Qingyao},
     booktitle = {Proceedings of the 49th International ACM SIGIR Conference on Research and Development in Information Retrieval},
     year = {2026},
     doi = {10.1145/3805712.3808611},
   }

2. ICLR

   What Scales in Cross-Entropy Scaling Law?

   Junxi Yan, Zixi Wei, Qingyao Ai, Yiqun Liu, and Jingtao Zhan^*

   In The Fourteenth International Conference on Learning Representations, 2026

   Bib PDF

   @inproceedings{yan2026scales,
     title = {What Scales in Cross-Entropy Scaling Law?},
     author = {Yan, Junxi and Wei, Zixi and Ai, Qingyao and Liu, Yiqun and Zhan, Jingtao},
     booktitle = {The Fourteenth International Conference on Learning Representations},
     year = {2026},
   }

2025

1. arXiv

   Evaluating Intelligence via Trial and Error

   Jingtao Zhan, Jiahao Zhao, Jiayu Li, Yiqun Liu, Bo Zhang, Qingyao Ai, Jiaxin Mao, Hongning Wang, Min Zhang, and Shaoping Ma

   arXiv preprint arXiv:2502.18858, 2025

   arXiv Bib

   @article{zhan2025evaluating,
     title = {Evaluating Intelligence via Trial and Error},
     author = {Zhan, Jingtao and Zhao, Jiahao and Li, Jiayu and Liu, Yiqun and Zhang, Bo and Ai, Qingyao and Mao, Jiaxin and Wang, Hongning and Zhang, Min and Ma, Shaoping},
     journal = {arXiv preprint arXiv:2502.18858},
     year = {2025},
   }

2024

1. SIGIR

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

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

   In Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

   DOI Bib

   @inproceedings{zhan2024capability,
     title = {Capability-aware Prompt Reformulation Learning for Text-to-Image Generation},
     author = {Zhan, Jingtao and Ai, Qingyao and Liu, Yiqun and Chen, Jia and Ma, Shaoping},
     booktitle = {Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval},
     year = {2024},
     doi = {10.1145/3626772.3657787},
   }

2. SIGIR

   Scaling Laws for Dense Retrieval

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

   In Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

   Best Paper Award DOI Bib

   Best Paper Award

   @inproceedings{fang2024scaling,
     title = {Scaling Laws for Dense Retrieval},
     author = {Fang, Yan and Zhan, Jingtao and Ai, Qingyao and Mao, Jiaxin and Su, Weihang and Chen, Jia and Liu, Yiqun},
     booktitle = {Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval},
     pages = {1339--1349},
     year = {2024},
     doi = {10.1145/3626772.3657743},
   }

3. AAAI

   Combining Multiple Supervision for Robust Zero-Shot Dense Retrieval

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

   In Proceedings of the AAAI Conference on Artificial Intelligence, 2024

   DOI Bib

   @inproceedings{fang2024combining,
     title = {Combining Multiple Supervision for Robust Zero-Shot Dense Retrieval},
     author = {Fang, Yan and Ai, Qingyao and Zhan, Jingtao and Liu, Yiqun and Wu, Xiaolong and Cao, Zhao},
     booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence},
     volume = {38},
     number = {16},
     pages = {17994--18002},
     year = {2024},
     doi = {10.1609/aaai.v38i16.29755},
   }

2023

1. SIGIR

   Constructing Tree-based Index for Efficient and Effective Dense Retrieval

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

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

   DOI arXiv Bib

   @inproceedings{li2023constructing,
     title = {Constructing Tree-based Index for Efficient and Effective Dense Retrieval},
     author = {Li, Haitao and Ai, Qingyao and Zhan, Jingtao and Mao, Jiaxin and Liu, Yiqun and Liu, Zheng and Cao, Zhao},
     booktitle = {Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval},
     pages = {131--140},
     year = {2023},
     doi = {10.1145/3539618.3591651},
   }

2022

1. arXiv

   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 preprint arXiv:2208.05753, 2022

   arXiv Bib

   @article{zhan2022disentangled,
     title = {Disentangled Modeling of Domain and Relevance for Adaptable Dense Retrieval},
     author = {Zhan, Jingtao and Ai, Qingyao and Liu, Yiqun and Mao, Jiaxin and Xie, Xiaohui and Zhang, Min and Ma, Shaoping},
     journal = {arXiv preprint arXiv:2208.05753},
     year = {2022},
   }

2. CIKM

   Evaluating Interpolation and Extrapolation Performance of Neural Retrieval Models

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

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

   DOI arXiv Bib

   @inproceedings{zhan2022evaluating,
     title = {Evaluating Interpolation and Extrapolation Performance of Neural Retrieval Models},
     author = {Zhan, Jingtao and Xie, Xiaohui and Mao, Jiaxin and Liu, Yiqun and Guo, Jiafeng and Zhang, Min and Ma, Shaoping},
     booktitle = {Proceedings of the 31st ACM International Conference on Information and Knowledge Management},
     pages = {2486--2496},
     year = {2022},
     doi = {10.1145/3511808.3557312},
   }

3. WSDM

   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

   In Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining, 2022

   Best Paper Award DOI Bib

   Best Paper Award

   @inproceedings{zhan2022learning,
     title = {Learning Discrete Representations via Constrained Clustering for Effective and Efficient Dense Retrieval},
     author = {Zhan, Jingtao and Mao, Jiaxin and Liu, Yiqun and Guo, Jiafeng and Zhang, Min and Ma, Shaoping},
     booktitle = {Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining},
     pages = {1328--1336},
     year = {2022},
     doi = {10.1145/3488560.3498443},
   }

2021

1. CIKM

   Jointly Optimizing Query Encoder and Product Quantization to Improve Retrieval Performance

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

   In Proceedings of the 30th ACM International Conference on Information and Knowledge Management, 2021

   DOI arXiv Bib

   @inproceedings{zhan2021jointly,
     title = {Jointly Optimizing Query Encoder and Product Quantization to Improve Retrieval Performance},
     author = {Zhan, Jingtao and Mao, Jiaxin and Liu, Yiqun and Guo, Jiafeng and Zhang, Min and Ma, Shaoping},
     booktitle = {Proceedings of the 30th ACM International Conference on Information and Knowledge Management},
     year = {2021},
     doi = {10.1145/3459637.3482358},
   }

2. SIGIR

   Optimizing Dense Retrieval Model Training with Hard Negatives

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

   In Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

   DOI arXiv Bib

   @inproceedings{zhan2021optimizing,
     title = {Optimizing Dense Retrieval Model Training with Hard Negatives},
     author = {Zhan, Jingtao and Mao, Jiaxin and Liu, Yiqun and Guo, Jiafeng and Zhang, Min and Ma, Shaoping},
     booktitle = {Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval},
     year = {2021},
     doi = {10.1145/3404835.3462880},
   }

2020

1. arXiv

   RepBERT: Contextualized Text Embeddings for First-Stage Retrieval

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

   arXiv preprint arXiv:2006.15498, 2020

   arXiv Bib

   @article{zhan2020repbert,
     title = {{RepBERT}: Contextualized Text Embeddings for First-Stage Retrieval},
     author = {Zhan, Jingtao and Mao, Jiaxin and Liu, Yiqun and Zhang, Min and Ma, Shaoping},
     journal = {arXiv preprint arXiv:2006.15498},
     year = {2020},
   }

2. SIGIR

   An Analysis of BERT in Document Ranking

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

   In Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, 2020

   DOI Bib

   @inproceedings{zhan2020analysis,
     title = {An Analysis of {BERT} in Document Ranking},
     author = {Zhan, Jingtao and Mao, Jiaxin and Liu, Yiqun and Zhang, Min and Ma, Shaoping},
     booktitle = {Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval},
     pages = {1941--1944},
     year = {2020},
     doi = {10.1145/3397271.3401325},
   }

3. WWW

   Leveraging Passage-level Cumulative Gain for Document Ranking

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

   In Proceedings of The Web Conference 2020, 2020

   DOI Bib

   @inproceedings{wu2020leveraging,
     title = {Leveraging Passage-level Cumulative Gain for Document Ranking},
     author = {Wu, Zhijing and Mao, Jiaxin and Liu, Yiqun and Zhan, Jingtao and Zheng, Yukun and Zhang, Min and Ma, Shaoping},
     booktitle = {Proceedings of The Web Conference 2020},
     pages = {2421--2431},
     year = {2020},
     doi = {10.1145/3366423.3380305},
   }