Huiying Li
About
In The Last Decade
Huiying Li
9 papers receiving 256 citations
Peers
Comparison fields: 5 of 51
- Artificial Intelligence 120
- Pharmacology 92
- Molecular Biology 82
- Inorganic Chemistry 71
- Oncology 29
Countries citing papers authored by Huiying Li
This map shows the geographic impact of Huiying Li'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 Huiying Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Huiying Li more than expected).
Fields of papers citing papers by Huiying Li
This network shows the impact of papers produced by Huiying Li. 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 Huiying Li. The network helps show where Huiying Li may publish in the future.
Co-authorship network of co-authors of Huiying Li
This figure shows the co-authorship network connecting the top 25 collaborators of Huiying Li. A scholar is included among the top collaborators of Huiying Li 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 Huiying Li. Huiying Li is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 16 | |
| 2 | 19 | |
| 3 | Persistent and Unforgeable Watermarks for Deep Neural Networks. | 6 |
| 4 | 2 | |
| 5 | 0 | |
| 6 | 148 | |
| 7 | A Structured Distributional Semantic Model for Event Co-reference | 11 |
| 8 | A Structured Distributional Semantic Model : Integrating Structure with Semantics | 4 |
| 9 | 2 | |
| 10 | Cross-Language Document Summarization Based on Machine Translation Quality Prediction | 62 |
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.