Qiantong Xu

2.2k total citations · 1 hit paper
12 papers, 730 citations indexed

About

Qiantong Xu is a scholar working on Artificial Intelligence, Signal Processing and Numerical Analysis. According to data from OpenAlex, Qiantong Xu has authored 12 papers receiving a total of 730 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 7 papers in Signal Processing and 1 paper in Numerical Analysis. Recurrent topics in Qiantong Xu's work include Speech Recognition and Synthesis (8 papers), Music and Audio Processing (6 papers) and Natural Language Processing Techniques (6 papers). Qiantong Xu is often cited by papers focused on Speech Recognition and Synthesis (8 papers), Music and Audio Processing (6 papers) and Natural Language Processing Techniques (6 papers). Qiantong Xu collaborates with scholars based in Israel, United States and China. Qiantong Xu's co-authors include Ronan Collobert, Gabriel Synnaeve, Vineel Pratap, Michael Auli, Alexei Baevski, Anuroop Sriram, Alexis Conneau, Juan Pino, Tatiana Likhomanenko and Kritika Singh and has published in prestigious 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).

In The Last Decade

Qiantong Xu

12 papers receiving 684 citations

Hit Papers

XLS-R: Self-supervised Cr... 2022 2026 2023 2024 2022 50 100 150 200 250

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Qiantong Xu Israel 7 643 311 80 46 26 12 730
Jaime Lorenzo-Trueba Spain 12 551 0.9× 366 1.2× 94 1.2× 60 1.3× 23 0.9× 33 658
Kushal Lakhotia Israel 10 830 1.3× 456 1.5× 94 1.2× 93 2.0× 30 1.2× 11 950
Yung-Sung Chuang Taiwan 10 643 1.0× 269 0.9× 100 1.3× 66 1.4× 17 0.7× 34 772
Kyu J. Han United States 12 371 0.6× 311 1.0× 44 0.6× 50 1.1× 11 0.4× 38 456
Larry Gillick United States 13 605 0.9× 390 1.3× 90 1.1× 47 1.0× 12 0.5× 32 723
Yossi Adi Israel 15 661 1.0× 395 1.3× 121 1.5× 65 1.4× 14 0.5× 56 838
Jenthe Thienpondt Belgium 6 792 1.2× 704 2.3× 75 0.9× 42 0.9× 32 1.2× 13 894
Jan Trmal United States 10 658 1.0× 411 1.3× 53 0.7× 57 1.2× 15 0.6× 23 716
Vimal Manohar United States 15 1.0k 1.6× 749 2.4× 49 0.6× 48 1.0× 28 1.1× 28 1.1k
Adithya Renduchintala United States 6 855 1.3× 544 1.7× 89 1.1× 45 1.0× 24 0.9× 17 934

Countries citing papers authored by Qiantong Xu

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

12 of 12 papers shown
1.
Li, Bo, et al.. (2024). SambaLingo: Teaching Large Language Models New Languages. 1–21. 3 indexed citations
2.
Xu, Qiantong, Alexei Baevski, & Michael Auli. (2022). Simple and Effective Zero-shot Cross-lingual Phoneme Recognition. Interspeech 2022. 2113–2117. 31 indexed citations
3.
Pratap, Vineel, Qiantong Xu, Tatiana Likhomanenko, Gabriel Synnaeve, & Ronan Collobert. (2022). Word Order does not Matter for Speech Recognition. ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 7202–7206. 3 indexed citations
4.
Babu, Arun, Changhan Wang, Andros Tjandra, et al.. (2022). XLS-R: Self-supervised Cross-lingual Speech Representation Learning at Scale. Interspeech 2022. 2278–2282. 266 indexed citations breakdown →
5.
Xu, Qiantong, Alexei Baevski, Tatiana Likhomanenko, et al.. (2021). Self-Training and Pre-Training are Complementary for Speech Recognition. 3030–3034. 83 indexed citations
6.
Xu, Qiantong, et al.. (2020). Spectral Frank-Wolfe Algorithm: Strict Complementarity and Linear Convergence. International Conference on Machine Learning. 1. 2535–2544. 4 indexed citations
7.
Xu, Qiantong, Tatiana Likhomanenko, Jacob Kahn, et al.. (2020). Iterative Pseudo-Labeling for Speech Recognition. 1006–1010. 63 indexed citations
8.
Pratap, Vineel, Qiantong Xu, Anuroop Sriram, Gabriel Synnaeve, & Ronan Collobert. (2020). MLS: A Large-Scale Multilingual Dataset for Speech Research. arXiv (Cornell University). 2757–2761. 171 indexed citations
9.
Pino, Juan, Qiantong Xu, Xutai Ma, Mohammad Javad Dousti, & Yun Tang. (2020). Self-Training for End-to-End Speech Translation. 1476–1480. 23 indexed citations
10.
Pratap, Vineel, Awni Hannun, Qiantong Xu, et al.. (2019). Wav2Letter++: A Fast Open-source Speech Recognition System. arXiv (Cornell University). 6460–6464. 78 indexed citations
11.
Wang, Lequn, Qiantong Xu, Christopher De, & Thorsten Joachims. (2018). Cost-Sensitive Learning via Deep Policy ERM. 1 indexed citations
12.
He, Zheng, et al.. (2017). Effects of meteorological factors on finger vein recognition. 1–8. 4 indexed citations

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.

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