Lianhui Qin
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 10%
- Information Systems
- Molecular Biology
- Signal Processing
- Co-authors
- Hai ZhaoZhisong ZhangYejin ChoiZhiting HuEric P. XingChandra BhagavatulaZhi‐Song ZhangRonan Le Bras
- Topics
- Topic Modeling (19 papers)Natural Language Processing Techniques (16 papers)Multimodal Machine Learning Applications (8 papers)
- Journals
- arXiv (Cornell University)PubMedProceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
- Partner nations
- United StatesChinaJapan
In The Last Decade
Lianhui Qin
20 papers receiving 465 citations
Peers
Comparison fields: 5 of 50
- Artificial Intelligence 445
- Computer Vision and Pattern Recognition 127
- Information Systems 26
- Molecular Biology 20
- Signal Processing 10
Countries citing papers authored by Lianhui Qin
This map shows the geographic impact of Lianhui Qin'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 Lianhui Qin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lianhui Qin more than expected).
Fields of papers citing papers by Lianhui Qin
This network shows the impact of papers produced by Lianhui Qin. 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 Lianhui Qin. The network helps show where Lianhui Qin may publish in the future.
Co-authorship network of co-authors of Lianhui Qin
This figure shows the co-authorship network connecting the top 25 collaborators of Lianhui Qin. A scholar is included among the top collaborators of Lianhui Qin 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 Lianhui Qin. Lianhui Qin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 6 | |
| 3 | 4 | |
| 4 | 11 | |
| 5 | 22 | |
| 6 | 52 | |
| 7 | 30 | |
| 8 | 27 | |
| 9 | Evaluating Machines by their Real-World Language Use | 5 |
| 10 | 24 | |
| 11 | 19 | |
| 12 | 56 | |
| 13 | 18 | |
| 14 | 12 | |
| 15 | 6 | |
| 16 | 63 | |
| 17 | Implicit Discourse Relation Recognition with Context-aware Character-enhanced Embeddings | 22 |
| 18 | 42 | |
| 19 | 45 | |
| 20 | 19 |
About Lianhui Qin
Lianhui Qin is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and General Social Sciences, having authored 20 papers that have together received 486 indexed citations. Recurring topics across this work include Topic Modeling (19 papers), Natural Language Processing Techniques (16 papers) and Multimodal Machine Learning Applications (8 papers). The work is most often cited by research in Artificial Intelligence (445 citations), Health Informatics (9 citations) and Computer Vision and Pattern Recognition (127 citations). Lianhui Qin has collaborated with scholars based in United States, China and Japan. Frequent co-authors include Hai Zhao, Zhisong Zhang, Yejin Choi, Zhiting Hu, Eric P. Xing, Chandra Bhagavatula, Zhi‐Song Zhang, Ronan Le Bras, Antoine Bosselut and Sean Welleck. Their work appears in journals such as arXiv (Cornell University), PubMed and Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies.
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.