Xiaojie Wang
- Computer Vision and Pattern Recognition top 1%
- Artificial Intelligence top 1%
- Management Science and Operations Research top 5%
- Media Technology top 5%
- Information Systems top 10%
- Topics
- Topic Modeling (52 papers)Natural Language Processing Techniques (38 papers)Multimodal Machine Learning Applications (36 papers)
- Partner nations
- ChinaUnited StatesJapan
In The Last Decade
Xiaojie Wang
124 papers receiving 1.8k citations
Hit Papers
Peers
Comparison fields: 5 of 92
- Computer Vision and Pattern Recognition 1.0k
- Artificial Intelligence 1000
- Management Science and Operations Research 122
- Media Technology 110
- Information Systems 85
Countries citing papers authored by Xiaojie Wang
This map shows the geographic impact of Xiaojie Wang'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 Xiaojie Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaojie Wang more than expected).
Fields of papers citing papers by Xiaojie Wang
This network shows the impact of papers produced by Xiaojie Wang. 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 Xiaojie Wang. The network helps show where Xiaojie Wang may publish in the future.
Co-authorship network of co-authors of Xiaojie Wang
This figure shows the co-authorship network connecting the top 25 collaborators of Xiaojie Wang. A scholar is included among the top collaborators of Xiaojie Wang 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 Xiaojie Wang. Xiaojie Wang 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 | 3 | |
| 3 | 2 | |
| 4 | 0 | |
| 5 | 3 | |
| 6 | 14 | |
| 7 | 86 | |
| 8 | 32 | |
| 9 | 2 | |
| 10 | Video description with integrated visual and textual information | 0 |
| 11 | 2 | |
| 12 | Chain of Reasoning for Visual Question Answering | 25 |
| 13 | RUCIR at NTCIR-12 IMINE-2 Task. | 1 |
| 14 | EXPLOITING LEXICAL INFORMATION FOR FUNCTION TAG LABELING | 0 |
| 15 | Apply Normalized Accessor Variety in Chinese Word Segmentation | 1 |
| 16 | 6 | |
| 17 | Multi-Task Learning in Conditional Random Fields for Chunking in Shallow Semantic Parsing | 1 |
| 18 | BUPT Systems in the SIGHAN Bakeoff 2007 | 3 |
| 19 | Word Segmentation and Named Entity Recognition for SIGHAN Bakeoff3 | 39 |
| 20 | Some Improvements on Maximum Entropy Based Chinese POS Tagging | 2 |
About Xiaojie Wang
Xiaojie Wang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology, having authored 149 papers that have together received 1.8k indexed citations. Recurring topics across this work include Topic Modeling (52 papers), Natural Language Processing Techniques (38 papers) and Multimodal Machine Learning Applications (36 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.0k citations), Artificial Intelligence (1000 citations) and Media Technology (110 citations). Xiaojie Wang has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Ruifan Li, Fangxiang Feng, Zhanyu Ma, Eduard Hovy, Hao Chen, Dong Xuan, Caixia Yuan, Chenfei Wu, Shibo Zhang and Peng Lu. Their work appears in journals such as Journal of Computational Physics, IEEE Transactions on Image Processing and IEEE Access.
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.