Richong Zhang
- Artificial Intelligence top 1%
- Information Systems top 2%
- Computer Vision and Pattern Recognition top 5%
- Computer Networks and Communications top 5%
- Statistical and Nonlinear Physics top 5%
- Topics
- Topic Modeling (54 papers)Natural Language Processing Techniques (27 papers)Advanced Graph Neural Networks (18 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE AccessInformation Sciences
- Partner nations
- ChinaCanadaUnited Kingdom
In The Last Decade
Richong Zhang
107 papers receiving 1.6k citations
Hit Papers
Peers
Comparison fields: 5 of 107
- Artificial Intelligence 1.2k
- Information Systems 434
- Computer Vision and Pattern Recognition 236
- Computer Networks and Communications 215
- Statistical and Nonlinear Physics 139
Countries citing papers authored by Richong Zhang
This map shows the geographic impact of Richong Zhang'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 Richong Zhang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Richong Zhang more than expected).
Fields of papers citing papers by Richong Zhang
This network shows the impact of papers produced by Richong Zhang. 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 Richong Zhang. The network helps show where Richong Zhang may publish in the future.
Co-authorship network of co-authors of Richong Zhang
This figure shows the co-authorship network connecting the top 25 collaborators of Richong Zhang. A scholar is included among the top collaborators of Richong Zhang 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 Richong Zhang. Richong Zhang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 2 | |
| 3 | 0 | |
| 4 | LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Modelsbreakdown → | 80 |
| 5 | 1 | |
| 6 | 4 | |
| 7 | 3 | |
| 8 | 8 | |
| 9 | 2 | |
| 10 | 1 | |
| 11 | 1 | |
| 12 | 1 | |
| 13 | 3 | |
| 14 | 9 | |
| 15 | Aspect-Level Sentiment Analysis Via Convolution over Dependency Treebreakdown → | 276 |
| 16 | The APVA-TURBO Approach To Question Answering in Knowledge Base | 12 |
| 17 | 37 | |
| 18 | On hyper-parameter estimation in empirical Bayes: a revisit of the MacKay algorithm | 1 |
| 19 | On the representation and embedding of knowledge bases beyond binary relations | 6 |
| 20 | Helpful or Unhelpful: A Linear Approach for Ranking Product Reviews | 23 |
About Richong Zhang
Richong Zhang is a scholar working on Artificial Intelligence, Information Systems and Statistical and Nonlinear Physics, having authored 118 papers that have together received 1.7k indexed citations. Recurring topics across this work include Topic Modeling (54 papers), Natural Language Processing Techniques (27 papers) and Advanced Graph Neural Networks (18 papers). The work is most often cited by research in Artificial Intelligence (1.2k citations), Information Systems (434 citations) and Computer Vision and Pattern Recognition (236 citations). Richong Zhang has collaborated with scholars based in China, Canada and United Kingdom. Frequent co-authors include Yongyi Mao, Samuel Mensah, Kai Sun, Xudong Liu, Hongyu Guo, Thomas Tran, Jinpeng Huai, Hailong Sun, Yaowei Zheng and Weiren Yu. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Access and Information Sciences.
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.