Daxin Jiang

12.0k total citations · 6 hit papers
129 papers, 5.8k citations indexed

About

Daxin Jiang is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Daxin Jiang has authored 129 papers receiving a total of 5.8k indexed citations (citations by other indexed papers that have themselves been cited), including 98 papers in Artificial Intelligence, 43 papers in Information Systems and 39 papers in Computer Vision and Pattern Recognition. Recurrent topics in Daxin Jiang's work include Topic Modeling (85 papers), Natural Language Processing Techniques (64 papers) and Multimodal Machine Learning Applications (32 papers). Daxin Jiang is often cited by papers focused on Topic Modeling (85 papers), Natural Language Processing Techniques (64 papers) and Multimodal Machine Learning Applications (32 papers). Daxin Jiang collaborates with scholars based in China, United States and Canada. Daxin Jiang's co-authors include Nan Duan, Ming Gong, Aidong Zhang, Jian Pei, Chun Tang, Duyu Tang, Linjun Shou, Ming Zhou, Daya Guo and Zhangyin Feng and has published in prestigious journals such as IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Knowledge and Data Engineering and Knowledge-Based Systems.

In The Last Decade

Daxin Jiang

122 papers receiving 5.5k citations

Hit Papers

CodeBERT: A Pre-Traine... 2004 2026 2011 2018 2020 2004 2020 2008 2021 400 800 1.2k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. CodeBERT: A Pre-Trained Model for Programming and Natural Languages
    2020 1.4k citations Daya Guo, Duyu Tang et al. profile →
  2. Cluster analysis for gene expression data: a survey
    2004 765 citations Daxin Jiang et al. profile →
  3. Unicoder-VL: A Universal Encoder for Vision and Language by Cross-Modal Pre-Training
    2020 479 citations Nan Duan, Ming Gong et al. Proceedings of the AAAI Conference on Artificial Intelligence profile →
  4. Context-aware query suggestion by mining click-through and session data
    2008 295 citations Daxin Jiang et al. profile →
  5. GraphCodeBERT: Pre-training Code Representations with Data Flow
    2021 261 citations Daya Guo, Duyu Tang et al. profile →
  6. K-Adapter: Infusing Knowledge into Pre-Trained Models with Adapters
    2021 218 citations Ruize Wang, Duyu Tang et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Daxin Jiang China 31 3.4k 2.4k 1.4k 774 749 129 5.8k
Duyu Tang China 30 6.3k 1.8× 2.2k 0.9× 598 0.4× 554 0.7× 333 0.4× 59 7.8k
Nan Duan China 37 4.4k 1.3× 2.1k 0.9× 1.8k 1.4× 599 0.8× 437 0.6× 155 6.8k
Xiaoyan Zhu China 38 5.1k 1.5× 1.3k 0.6× 669 0.5× 212 0.3× 223 0.3× 171 6.4k
Ting Liu China 31 4.8k 1.4× 1.6k 0.7× 429 0.3× 418 0.5× 177 0.2× 127 5.8k
Yangqiu Song China 39 4.1k 1.2× 1.2k 0.5× 1.8k 1.3× 555 0.7× 278 0.4× 221 5.7k
Baowen Xu China 40 2.4k 0.7× 4.9k 2.1× 459 0.3× 734 0.9× 258 0.3× 397 7.9k
Zhi Jin China 30 3.0k 0.9× 2.9k 1.2× 434 0.3× 703 0.9× 149 0.2× 304 5.1k
Zhoujun Li China 40 3.5k 1.0× 1.3k 0.5× 1.1k 0.8× 342 0.4× 253 0.3× 338 5.2k
Eric Brill United States 32 5.7k 1.6× 2.1k 0.9× 717 0.5× 635 0.8× 353 0.5× 61 7.0k
William B. Frakes United States 19 2.0k 0.6× 2.2k 0.9× 321 0.2× 397 0.5× 124 0.2× 55 3.5k

Countries citing papers authored by Daxin Jiang

Since Specialization
Citations

This map shows the geographic impact of Daxin Jiang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Daxin Jiang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daxin Jiang more than expected).

Fields of papers citing papers by Daxin Jiang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daxin Jiang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Daxin Jiang. The network helps show where Daxin Jiang may publish in the future.

Co-authorship network of co-authors of Daxin Jiang

This figure shows the co-authorship network connecting the top 25 collaborators of Daxin Jiang. A scholar is included among the top collaborators of Daxin Jiang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Daxin Jiang. Daxin Jiang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
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Tao, Chongyang, Chang Liu, Tao Shen, et al.. (2024). ADAM: Dense Retrieval Distillation with Adaptive Dark Examples. 11639–11651. 1 indexed citations
4.
Zhou, Yucheng, Tao Shen, Xiubo Geng, et al.. (2024). Fine-Grained Distillation for Long Document Retrieval. Proceedings of the AAAI Conference on Artificial Intelligence. 38(17). 19732–19740. 2 indexed citations
5.
Tao, Chongyang, Xiubo Geng, Tao Shen, et al.. (2024). Synergistic Interplay between Search and Large Language Models for Information Retrieval. 9571–9583. 2 indexed citations
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Gong, Ming, et al.. (2023). Instructed Language Models with Retrievers Are Powerful Entity Linkers. 2267–2282. 2 indexed citations
8.
Sun, Hao, Xiao Liu, Yeyun Gong, et al.. (2023). Allies: Prompting Large Language Model with Beam Search. 3794–3805. 2 indexed citations
9.
Gong, Yeyun, et al.. (2023). PROD: Progressive Distillation for Dense Retrieval. 3299–3308. 11 indexed citations
10.
Li, Xiaonan, Daya Guo, Yeyun Gong, et al.. (2022). Soft-Labeled Contrastive Pre-Training for Function-Level Code Representation. 118–129. 5 indexed citations
11.
Wang, Yong, Shilin He, Guanhua Chen, Yun Chen, & Daxin Jiang. (2022). XLM-D: Decorate Cross-lingual Pre-training Model as Non-Autoregressive Neural Machine Translation. 6934–6946. 2 indexed citations
12.
Li, Xiaonan, Yeyun Gong, Yelong Shen, et al.. (2022). CodeRetriever: A Large Scale Contrastive Pre-Training Method for Code Search. 2898–2910. 11 indexed citations
13.
Shou, Linjun, et al.. (2022). Empowering Dual-Encoder with Query Generator for Cross-Lingual Dense Retrieval. 3107–3121. 4 indexed citations
14.
Wang, Siyuan, Wanjun Zhong, Duyu Tang, et al.. (2022). Logic-Driven Context Extension and Data Augmentation for Logical Reasoning of Text. Findings of the Association for Computational Linguistics: ACL 2022. 1619–1629. 16 indexed citations
15.
Sun, Qing‐Feng, Yujing Wang, Can Xu, et al.. (2022). Multimodal Dialogue Response Generation. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2854–2866. 14 indexed citations
16.
Liu, Qian, Xiubo Geng, Yu Wang, Erik Cambria, & Daxin Jiang. (2022). Disentangled Retrieval and Reasoning for Implicit Question Answering. IEEE Transactions on Neural Networks and Learning Systems. 35(6). 7804–7815. 7 indexed citations
17.
Wang, Ruize, Duyu Tang, Nan Duan, et al.. (2021). K-Adapter: Infusing Knowledge into Pre-Trained Models with Adapters. 1405–1418. 218 indexed citations breakdown →
18.
Yang, Nan, et al.. (2021). xMoCo: Cross Momentum Contrastive Learning for Open-Domain Question Answering. 6120–6129. 19 indexed citations
19.
Guo, Daya, Duyu Tang, Qinliang Su, et al.. (2021). Syntax-Enhanced Pre-trained Model. 5412–5422. 20 indexed citations
20.
Zheng, Chujie, Yunbo Cao, Daxin Jiang, & Minlie Huang. (2020). Difference-aware Knowledge Selection for Knowledge-grounded Conversation Generation. 115–125. 27 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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