Qiantong Xu
- Artificial Intelligence top 2%
- Signal Processing top 2%
- Computer Vision and Pattern Recognition top 10%
- Experimental and Cognitive Psychology
- Physiology
- Co-authors
- Gabriel SynnaeveRonan CollobertVineel PratapAlexei BaevskiMichael AuliAnuroop SriramAlexis ConneauJuan Pino
- Topics
- Speech Recognition and Synthesis (8 papers)Music and Audio Processing (6 papers)Natural Language Processing Techniques (6 papers)
- Journals
- arXiv (Cornell University)International Conference on Machine LearningICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
- Partner nations
- IsraelUnited StatesChina
In The Last Decade
Qiantong Xu
12 papers receiving 684 citations
Hit Papers
Peers
Comparison fields: 5 of 72
- Artificial Intelligence 643
- Signal Processing 311
- Computer Vision and Pattern Recognition 80
- Experimental and Cognitive Psychology 46
- Physiology 26
Countries citing papers authored by Qiantong Xu
This map shows the geographic impact of Qiantong Xu'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 Qiantong Xu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qiantong Xu more than expected).
Fields of papers citing papers by Qiantong Xu
This network shows the impact of papers produced by Qiantong Xu. 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 Qiantong Xu. The network helps show where Qiantong Xu may publish in the future.
Co-authorship network of co-authors of Qiantong Xu
This figure shows the co-authorship network connecting the top 25 collaborators of Qiantong Xu. A scholar is included among the top collaborators of Qiantong Xu 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 Qiantong Xu. Qiantong Xu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 31 | |
| 3 | 3 | |
| 4 | XLS-R: Self-supervised Cross-lingual Speech Representation Learning at Scalebreakdown → | 266 |
| 5 | 83 | |
| 6 | 171 | |
| 7 | 63 | |
| 8 | Spectral Frank-Wolfe Algorithm: Strict Complementarity and Linear Convergence | 4 |
| 9 | 23 | |
| 10 | 78 | |
| 11 | Cost-Sensitive Learning via Deep Policy ERM | 1 |
| 12 | 4 |
About Qiantong Xu
Qiantong Xu is a scholar working on Signal Processing, Artificial Intelligence and Numerical Analysis, having authored 12 papers that have together received 730 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (8 papers), Music and Audio Processing (6 papers) and Natural Language Processing Techniques (6 papers). The work is most often cited by research in Signal Processing (311 citations), Artificial Intelligence (643 citations) and Computer Vision and Pattern Recognition (80 citations). Qiantong Xu has collaborated with scholars based in Israel, United States and China. Frequent co-authors include Gabriel Synnaeve, Ronan Collobert, Vineel Pratap, Alexei Baevski, Michael Auli, Anuroop Sriram, Alexis Conneau, Juan Pino, Tatiana Likhomanenko and Awni Hannun. Their work appears in journals such as arXiv (Cornell University), International Conference on Machine Learning and ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
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.