Xiaobo Liang
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition
- Information Systems
- Computational Theory and Mathematics
- Molecular Biology
- Topics
- Topic Modeling (10 papers)Natural Language Processing Techniques (10 papers)Multimodal Machine Learning Applications (3 papers)
- Cited by
- Artificial IntelligenceComputer Vision and Pattern RecognitionComputational Theory and Mathematics
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceArtificial IntelligenceBriefings in Bioinformatics
- Partner nations
- ChinaUnited StatesGermany
In The Last Decade
Xiaobo Liang
16 papers receiving 154 citations
Peers
Comparison fields: 5 of 47
- Artificial Intelligence 124
- Computer Vision and Pattern Recognition 23
- Information Systems 21
- Computational Theory and Mathematics 17
- Molecular Biology 15
Countries citing papers authored by Xiaobo Liang
This map shows the geographic impact of Xiaobo Liang'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 Xiaobo Liang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaobo Liang more than expected).
Fields of papers citing papers by Xiaobo Liang
This network shows the impact of papers produced by Xiaobo Liang. 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 Xiaobo Liang. The network helps show where Xiaobo Liang may publish in the future.
Co-authorship network of co-authors of Xiaobo Liang
This figure shows the co-authorship network connecting the top 25 collaborators of Xiaobo Liang. A scholar is included among the top collaborators of Xiaobo Liang 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 Xiaobo Liang. Xiaobo Liang 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 | 0 | |
| 3 | 4 | |
| 4 | 1 | |
| 5 | 5 | |
| 6 | 5 | |
| 7 | 5 | |
| 8 | 4 | |
| 9 | 14 | |
| 10 | 2 | |
| 11 | 17 | |
| 12 | 87 | |
| 13 | 3 | |
| 14 | Neural Relation Classification with Text Descriptions | 7 |
| 15 | A Multiple Utterances based Neural Network Model for Joint Intent Detection and Slot Filling. | 1 |
| 16 | An Enhanced ESIM Model for Sentence Pair Matching with Self-Attention. | 2 |
| 17 | 2 | |
| 18 | AN EFFICIENT LEARNING ALGORITHM FOR ASSOCIATIVE MEMORY NEURAL NETWORK | 1 |
About Xiaobo Liang
Xiaobo Liang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Pharmacology, having authored 18 papers that have together received 160 indexed citations. Recurring topics across this work include Topic Modeling (10 papers), Natural Language Processing Techniques (10 papers) and Multimodal Machine Learning Applications (3 papers). The work is most often cited by research in Artificial Intelligence (124 citations), Computer Vision and Pattern Recognition (23 citations) and Computational Theory and Mathematics (17 citations). Xiaobo Liang has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Yue Zhang, Jia Chen, Lijun Wu, Juntao Li, Min Zhang, Tie‐Yan Liu, Tao Qin, Yingce Xia, Shufang Xie and Jinhua Zhu. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Artificial Intelligence and Briefings in Bioinformatics.
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.