Daya Guo
Impact in
- Software top 0.5%
- Software Testing and Debugging Techniques
- Software Reliability and Analysis Research
- Information Systems top 0.2%
- Software Engineering Research
Papers in
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- Topic Modeling 13
- Natural Language Processing Techniques 10
- Text Readability and Simplification 2
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- Software Engineering Research 4
- Web Data Mining and Analysis 2
- Co-authors
- Nan Duan (14 shared papers)Ming Zhou (7 shared papers)Duyu Tang (9 shared papers)Daxin Jiang (7 shared papers)Zhangyin Feng (2 shared papers)Linjun Shou (3 shared papers)Ming Gong (3 shared papers)Ting Liu (1 shared paper)
- Journals
- IEEE Transactions on Software Engineering (2 papers)Automated Software Engineering (1 paper)Findings of the Association for Computational Linguistics: ACL 2022 (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)UTS ePRESS (University of Technology Sydney) (1 paper)
- Partner nations
- ChinaUnited KingdomUnited States
In The Last Decade
Daya Guo
19 papers receiving 2.5k citations
Daya Guo's Hit Papers
Peers
Comparison fields: 5 of 69
- Software 813
- Information Systems 1.6k
- Signal Processing 508
- Artificial Intelligence 1.3k
- Health Informatics 29
Countries citing papers authored by Daya Guo
This map shows the geographic impact of Daya Guo'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 Daya Guo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daya Guo more than expected).
Fields of papers citing papers by Daya Guo
This network shows the impact of papers produced by Daya Guo. 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 Daya Guo. The network helps show where Daya Guo may publish in the future.
Co-authors
The 25 scholars most cited alongside Daya Guo, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | CodeBERT: A Pre-Trained Model for Programming and Natural Languages Hit paper breakdown → | 2020 | 1459 |
| 2 | UniXcoder: Unified Cross-Modal Pre-training for Code Representation Hit paper breakdown → | 2022 | 332 |
| 3 | GraphCodeBERT: Pre-training Code Representations with Data Flow Hit paper breakdown → | 2021 | 268 |
| 4 | 2020 | 117 | |
| 5 | Automating code review activities by large-scale pre-training Hit paper breakdown → | 2022 | 97 |
| 6 | 2023 | 64 | |
| 7 | 2019 | 54 | |
| 8 | Dialog-to-action: conversational question answering over a large-scale knowledge base | 2018 | 44 |
| 9 | 2018 | 34 | |
| 10 | 2021 | 22 | |
| 11 | 2022 | 15 | |
| 12 | 2024 | 8 | |
| 13 | 2020 | 7 | |
| 14 | 2022 | 5 | |
| 15 | 2019 | 5 | |
| 16 | 2025 | 5 | |
| 17 | 2022 | 4 | |
| 18 | 2025 | 2 | |
| 19 | 2023 | 1 | |
| 20 | 2025 | 0 |
About Daya Guo
Daya Guo is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Computer Networks and Communications and Software, having authored 21 papers that have together received 2.5k indexed citations. Recurring topics across this work include Topic Modeling (13 papers), Natural Language Processing Techniques (10 papers), Multimodal Machine Learning Applications (5 papers), Software Engineering Research (4 papers), Web Data Mining and Analysis (2 papers), Text Readability and Simplification (2 papers), Advanced Image and Video Retrieval Techniques (2 papers) and Software Testing and Debugging Techniques (2 papers). The work is most often cited by research in Software (813 citations), Information Systems (1.6k citations), Signal Processing (508 citations), Artificial Intelligence (1.3k citations) and Health Informatics (29 citations). Daya Guo has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Nan Duan, Ming Zhou, Duyu Tang, Daxin Jiang, Zhangyin Feng, Linjun Shou, Ming Gong, Ting Liu, Bing Qin and Xiaocheng Feng. Their work appears in journals such as IEEE Transactions on Software Engineering, Automated Software Engineering, Findings of the Association for Computational Linguistics: ACL 2022, Proceedings of the AAAI Conference on Artificial Intelligence and UTS ePRESS (University of Technology Sydney).
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.