Tiezheng Yu
- Artificial Intelligence top 0.5%
- Health Informatics top 0.1%
- Information Systems top 2%
- Computer Vision and Pattern Recognition top 5%
- Sociology and Political Science top 10%
- Topics
- Topic Modeling (14 papers)Natural Language Processing Techniques (11 papers)Multimodal Machine Learning Applications (4 papers)
- Journals
- ACM Computing SurveysEurope PMC (PubMed Central)Rare & Special e-Zone (The Hong Kong University of Science and Technology)
In The Last Decade
Tiezheng Yu
18 papers receiving 2.1k citations
Hit Papers
Peers
Comparison fields: 5 of 148
- Artificial Intelligence 1.4k
- Health Informatics 382
- Information Systems 277
- Computer Vision and Pattern Recognition 204
- Sociology and Political Science 157
Countries citing papers authored by Tiezheng Yu
This map shows the geographic impact of Tiezheng Yu'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 Tiezheng Yu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tiezheng Yu more than expected).
Fields of papers citing papers by Tiezheng Yu
This network shows the impact of papers produced by Tiezheng Yu. 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 Tiezheng Yu. The network helps show where Tiezheng Yu may publish in the future.
Co-authorship network of co-authors of Tiezheng Yu
This figure shows the co-authorship network connecting the top 25 collaborators of Tiezheng Yu. A scholar is included among the top collaborators of Tiezheng Yu 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 Tiezheng Yu. Tiezheng Yu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 89 | |
| 3 | 1 | |
| 4 | 16 | |
| 5 | A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivitybreakdown → | 388 |
| 6 | 1 | |
| 7 | 2 | |
| 8 | 2 | |
| 9 | Survey of Hallucination in Natural Language Generationbreakdown → | 1469 |
| 10 | 3 | |
| 11 | 5 | |
| 12 | 38 | |
| 13 | 49 | |
| 14 | 75 | |
| 15 | 13 | |
| 16 | 2 | |
| 17 | CAiRE-COVID: A Question Answering and Multi-Document Summarization System for COVID-19 Research. | 12 |
| 18 | 12 | |
| 19 | 51 |
About Tiezheng Yu
Tiezheng Yu is a scholar working on Health Informatics, Artificial Intelligence and General Social Sciences, having authored 19 papers that have together received 2.2k indexed citations. Recurring topics across this work include Topic Modeling (14 papers), Natural Language Processing Techniques (11 papers) and Multimodal Machine Learning Applications (4 papers). The work is most often cited by research in Health Informatics (382 citations), Artificial Intelligence (1.4k citations) and Computer Science Applications (99 citations). Tiezheng Yu has collaborated with scholars based in Hong Kong, Greece and China. Frequent co-authors include Pascale Fung, Ziwei Ji, Yan Xu, Dan Su, Nayeon Lee, Etsuko Ishii, Andrea Madotto, Rita Frieske, Wenliang Dai and Samuel Cahyawijaya. Their work appears in journals such as ACM Computing Surveys, Europe PMC (PubMed Central) and Rare & Special e-Zone (The Hong Kong University of Science and Technology).
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.