Следене
Jingtao Zhan
Jingtao Zhan
Потвърден имейл адрес: mails.tsinghua.edu.cn - Начална страница
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Позовавания
Позовавания
Година
Optimizing Dense Retrieval Model Training with Hard Negatives
J Zhan, J Mao, Y Liu, J Guo, M Zhang, S Ma
Proceedings of the 44th International ACM SIGIR Conference on Research and …, 2021
2212021
Repbert: Contextualized text embeddings for first-stage retrieval
J Zhan, J Mao, Y Liu, M Zhang, S Ma
arXiv preprint arXiv:2006.15498, 2020
1132020
Jointly Optimizing Query Encoder and Product Quantization to Improve Retrieval Performance
J Zhan, J Mao, Y Liu, J Guo, M Zhang, S Ma
Proceedings of the 30th ACM International Conference on Information and …, 2021
572021
Learning discrete representations via constrained clustering for effective and efficient dense retrieval
J Zhan, J Mao, Y Liu, J Guo, M Zhang, S Ma
Proceedings of the Fifteenth ACM International Conference on Web Search and …, 2022
512022
Leveraging passage-level cumulative gain for document ranking
Z Wu, J Mao, Y Liu, J Zhan, Y Zheng, M Zhang, S Ma
Proceedings of the web conference 2020, 2421-2431, 2020
412020
An Analysis of BERT in Document Ranking
J Zhan, J Mao, Y Liu, M Zhang, S Ma
Proceedings of the 43rd International ACM SIGIR Conference on Research and …, 2020
382020
Learning to retrieve: How to train a dense retrieval model effectively and efficiently
J Zhan, J Mao, Y Liu, M Zhang, S Ma
arXiv preprint arXiv:2010.10469, 2020
262020
Evaluating interpolation and extrapolation performance of neural retrieval models
J Zhan, X Xie, J Mao, Y Liu, J Guo, M Zhang, S Ma
Proceedings of the 31st ACM International Conference on Information …, 2022
16*2022
THUIR at the NTCIR-16 WWW-4 task
S Yang, H Li, Z Chu, J Zhan, Y Liu, M Zhang, S Ma
Proceedings of NTCIR-16. to appear, 2022
112022
Constructing tree-based index for efficient and effective dense retrieval
H Li, Q Ai, J Zhan, J Mao, Y Liu, Z Liu, Z Cao
Proceedings of the 46th International ACM SIGIR Conference on Research and …, 2023
92023
Disentangled modeling of domain and relevance for adaptable dense retrieval
J Zhan, Q Ai, Y Liu, J Mao, X Xie, M Zhang, S Ma
arXiv preprint arXiv:2208.05753, 2022
82022
Interpreting dense retrieval as mixture of topics
J Zhan, J Mao, Y Liu, J Guo, M Zhang, S Ma
arXiv preprint arXiv:2111.13957, 2021
52021
Joint Optimization of Multi-vector Representation with Product Quantization
Y Fang, J Zhan, Y Liu, J Mao, M Zhang, S Ma
CCF International Conference on Natural Language Processing and Chinese …, 2022
22022
THUIR at the NTCIR-15 WWW-3 Task
Z Chu, J Zhan, X Li, J Mao, Y Liu, M Zhang, S Ma
Proceedings of NTCIR-15, 249-252, 2020
12020
Query Augmentation by Decoding Semantics from Brain Signals
Z Ye, J Zhan, Q Ai, Y Liu, M de Rijke, C Lioma, T Ruotsalo
arXiv preprint arXiv:2402.15708, 2024
2024
Combining Multiple Supervision for Robust Zero-shot Dense Retrieval
Y Fang, Q Ai, J Zhan, Y Liu, X Wu, Z Cao
2024
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