Kai-Wei Chang
Impact in
- Artificial Intelligence top 0.1%
- Topic Modeling
- Natural Language Processing Techniques
- Adversarial Robustness in Machine Learning
- Hate Speech and Cyberbullying Detection
- Advanced Graph Neural Networks
- Health Informatics top 0.5%
Papers in
-
- Topic Modeling 109
- Natural Language Processing Techniques 76
- Adversarial Robustness in Machine Learning 20
- Domain Adaptation and Few-Shot Learning 20
- Machine Learning and Data Classification 11
- Advanced Text Analysis Techniques 9
- Explainable Artificial Intelligence (XAI) 8
-
- Multimodal Machine Learning Applications 34
- Co-authors
- Wasi Uddin AhmadJieyu ZhaoNanyun PengMark YatskarAdam Tauman KalaiJames ZouVenkatesh SaligramaStéphane Richard
- Journals
- Transactions of the Association for Computational Linguistics (2 papers)American Journal of Public Health (2 papers)Bioinformatics (1 paper)Nature Communications (1 paper)Language Resources and Evaluation (1 paper)
- Partner nations
- United StatesChinaUnited Kingdom
In The Last Decade
Kai-Wei Chang
161 papers receiving 5.9k citations
Hit Papers
Peers
Comparison fields: 5 of 174
- Artificial Intelligence 4.2k
- Health Informatics 159
- Software 202
- Safety Research 409
- General Social Sciences 159
Countries citing papers authored by Kai-Wei Chang
This map shows the geographic impact of Kai-Wei Chang'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 Kai-Wei Chang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kai-Wei Chang more than expected).
Fields of papers citing papers by Kai-Wei Chang
This network shows the impact of papers produced by Kai-Wei Chang. 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 Kai-Wei Chang. The network helps show where Kai-Wei Chang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Kai-Wei Chang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 2 | |
| 2 | 2024 | 0 | |
| 3 | 2024 | 3 | |
| 4 | 2024 | 0 | |
| 5 | 2024 | 7 | |
| 6 | 2024 | 0 | |
| 7 | 2024 | 2 | |
| 8 | 2024 | 2 | |
| 9 | 2024 | 0 | |
| 10 | 2024 | 3 | |
| 11 | 2022 | 23 | |
| 12 | 2022 | 21 | |
| 13 | 2022 | 16 | |
| 14 | 2021 | 81 | |
| 15 | 2021 | 79 | |
| 16 | 2019 | 216 | |
| 17 | 2019 | 214 | |
| 18 | 2018 | 181 | |
| 19 | 2013 | 36 | |
| 20 | Inference Protocols for Coreference Resolution | 2011 | 22 |
About Kai-Wei Chang
Kai-Wei Chang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, General Social Sciences, Computational Mathematics and Information Systems, having authored 189 papers that have together received 6.2k indexed citations. Recurring topics across this work include Topic Modeling (109 papers), Natural Language Processing Techniques (76 papers), Multimodal Machine Learning Applications (34 papers), Adversarial Robustness in Machine Learning (20 papers), Domain Adaptation and Few-Shot Learning (20 papers), Machine Learning and Data Classification (11 papers), Advanced Text Analysis Techniques (9 papers) and Explainable Artificial Intelligence (XAI) (8 papers). The work is most often cited by research in Artificial Intelligence (4.2k citations), Health Informatics (159 citations), Software (202 citations), Safety Research (409 citations) and General Social Sciences (159 citations). Kai-Wei Chang has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Wasi Uddin Ahmad, Jieyu Zhao, Nanyun Peng, Mark Yatskar, Adam Tauman Kalai, James Zou, Venkatesh Saligrama, Stéphane Richard, Kiven Erique Lukong and Tolga Bolukbasi. Their work appears in journals such as Transactions of the Association for Computational Linguistics, American Journal of Public Health, Bioinformatics, Nature Communications and Language Resources and Evaluation.
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.