Shijie Geng
- Artificial Intelligence top 2%
- Computer Vision and Pattern Recognition top 2%
- Information Systems top 2%
- Radiology, Nuclear Medicine and Imaging
- Management Science and Operations Research top 10%
- Topics
- Advanced Image and Video Retrieval Techniques (8 papers)Multimodal Machine Learning Applications (8 papers)Topic Modeling (6 papers)
- Journals
- Environmental PollutionInternational Journal of Computer VisionProceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
- Partner nations
- United StatesChinaNetherlands
In The Last Decade
Shijie Geng
20 papers receiving 899 citations
Hit Papers
Peers
Comparison fields: 5 of 84
- Artificial Intelligence 621
- Computer Vision and Pattern Recognition 390
- Information Systems 305
- Radiology, Nuclear Medicine and Imaging 52
- Management Science and Operations Research 43
Countries citing papers authored by Shijie Geng
This map shows the geographic impact of Shijie Geng'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 Shijie Geng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shijie Geng more than expected).
Fields of papers citing papers by Shijie Geng
This network shows the impact of papers produced by Shijie Geng. 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 Shijie Geng. The network helps show where Shijie Geng may publish in the future.
Co-authorship network of co-authors of Shijie Geng
This figure shows the co-authorship network connecting the top 25 collaborators of Shijie Geng. A scholar is included among the top collaborators of Shijie Geng 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 Shijie Geng. Shijie Geng 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 | 28 | |
| 3 | CLIP-Adapter: Better Vision-Language Models with Feature Adaptersbreakdown → | 402 |
| 4 | 15 | |
| 5 | 4 | |
| 6 | 20 | |
| 7 | 46 | |
| 8 | 49 | |
| 9 | 7 | |
| 10 | Recommendation as Language Processing (RLP): A Unified Pretrain, Personalized Prompt & Predict Paradigm (P5)breakdown → | 223 |
| 11 | 22 | |
| 12 | 7 | |
| 13 | 11 | |
| 14 | 5 | |
| 15 | 10 | |
| 16 | 15 | |
| 17 | 11 | |
| 18 | 2 | |
| 19 | 6 | |
| 20 | 6 |
About Shijie Geng
Shijie Geng is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Information Systems, having authored 21 papers that have together received 916 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (8 papers), Multimodal Machine Learning Applications (8 papers) and Topic Modeling (6 papers). The work is most often cited by research in Artificial Intelligence (621 citations), Computer Vision and Pattern Recognition (390 citations) and Information Systems (305 citations). Shijie Geng has collaborated with scholars based in United States, China and Netherlands. Frequent co-authors include Yongfeng Zhang, Zuohui Fu, Yingqiang Ge, Shuchang Liu, Yu Qiao, Peng Gao, Hongsheng Li, Teli Ma, Rongyao Fang and Renrui Zhang. Their work appears in journals such as Environmental Pollution, International Journal of Computer Vision and Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers).
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.