Zalán Borsos

711 total citations · 1 hit paper
10 papers, 317 citations indexed

About

Zalán Borsos is a scholar working on Artificial Intelligence, Signal Processing and Information Systems. According to data from OpenAlex, Zalán Borsos has authored 10 papers receiving a total of 317 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 4 papers in Signal Processing and 1 paper in Information Systems. Recurrent topics in Zalán Borsos's work include Speech Recognition and Synthesis (5 papers), Speech and Audio Processing (4 papers) and Music and Audio Processing (4 papers). Zalán Borsos is often cited by papers focused on Speech Recognition and Synthesis (5 papers), Speech and Audio Processing (4 papers) and Music and Audio Processing (4 papers). Zalán Borsos collaborates with scholars based in Switzerland, United States and Romania. Zalán Borsos's co-authors include Marco Tagliasacchi, Neil Zeghidour, Olivier Pietquin, Matt Sharifi, Raphaël Marinier, Eugene Kharitonov, Damien Vincent, Dominik Roblek, Olivier Teboul and David Grangier and has published in prestigious journals such as IEEE/ACM Transactions on Audio Speech and Language Processing, Transactions of the Association for Computational Linguistics and Pattern Analysis and Applications.

In The Last Decade

Zalán Borsos

10 papers receiving 301 citations

Hit Papers

AudioLM: A Language Modeling Approach to Audio Generation 2023 2026 2024 2025 2023 50 100 150 200

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Zalán Borsos Switzerland 6 220 145 71 13 12 10 317
Raphaël Marinier United States 5 203 0.9× 122 0.8× 84 1.2× 6 0.5× 17 1.4× 7 319
Matt Sharifi United States 4 179 0.8× 154 1.1× 83 1.2× 4 0.3× 13 1.1× 4 298
Khawar Mehmood Pakistan 5 225 1.0× 65 0.4× 35 0.5× 14 1.1× 10 0.8× 8 294
Yatharth Saraf United States 9 385 1.8× 225 1.6× 57 0.8× 8 0.6× 5 0.4× 17 459
A. Revathi India 9 133 0.6× 181 1.2× 70 1.0× 21 1.6× 26 2.2× 53 276
Tom Bagby United States 7 359 1.6× 245 1.7× 34 0.5× 16 1.2× 6 0.5× 7 402
Mike Seltzer United States 7 265 1.2× 196 1.4× 45 0.6× 6 0.5× 4 0.3× 17 311
Andrew Morris Switzerland 10 284 1.3× 250 1.7× 54 0.8× 8 0.6× 18 1.5× 25 384
Damien Vincent France 8 249 1.1× 218 1.5× 273 3.8× 9 0.7× 16 1.3× 12 551

Countries citing papers authored by Zalán Borsos

Since Specialization
Citations

This map shows the geographic impact of Zalán Borsos'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 Zalán Borsos with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zalán Borsos more than expected).

Fields of papers citing papers by Zalán Borsos

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Zalán Borsos. 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 Zalán Borsos. The network helps show where Zalán Borsos may publish in the future.

Co-authorship network of co-authors of Zalán Borsos

This figure shows the co-authorship network connecting the top 25 collaborators of Zalán Borsos. A scholar is included among the top collaborators of Zalán Borsos 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 Zalán Borsos. Zalán Borsos is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

10 of 10 papers shown
1.
Borsos, Zalán, Raphaël Marinier, Damien Vincent, et al.. (2023). AudioLM: A Language Modeling Approach to Audio Generation. IEEE/ACM Transactions on Audio Speech and Language Processing. 31. 2523–2533. 201 indexed citations breakdown →
2.
Kharitonov, Eugene, Damien Vincent, Zalán Borsos, et al.. (2023). Speak, Read and Prompt: High-Fidelity Text-to-Speech with Minimal Supervision. Transactions of the Association for Computational Linguistics. 11. 1703–1718. 54 indexed citations
3.
Zeghidour, Neil, et al.. (2023). Disentangling Speech from Surroundings with Neural Embeddings. 1–5. 6 indexed citations
4.
Kleijn, W. Bastiaan, et al.. (2023). LMCodec: A Low Bitrate Speech Codec with Causal Transformer Models. 1–5. 15 indexed citations
5.
Erdoğan, Hakan, Scott Wisdom, Xuankai Chang, et al.. (2023). TokenSplit: Using Discrete Speech Representations for Direct, Refined, and Transcript-Conditioned Speech Separation and Recognition. 3462–3466. 2 indexed citations
6.
Borsos, Zalán, et al.. (2022). SpeechPainter: Text-conditioned Speech Inpainting. Interspeech 2022. 431–435. 14 indexed citations
7.
Borsos, Zalán, Mojmír Mutný, & Andreas Krause. (2020). Coresets via Bilevel Optimization for Continual Learning and Streaming. arXiv (Cornell University). 33. 14879–14890. 2 indexed citations
8.
Borsos, Zalán, et al.. (2019). Online Variance Reduction with Mixtures. arXiv (Cornell University). 97. 705–714. 1 indexed citations
9.
Borsos, Zalán, Camelia Lemnaru, & Rodica Potolea. (2016). Dealing with overlap and imbalance: a new metric and approach. Pattern Analysis and Applications. 21(2). 381–395. 19 indexed citations
10.
Creţ, Octavian, et al.. (2013). Implementing Modular FFTs in FPGAs -- A Basic Block for Lattice-Based Cryptography. 305–308. 3 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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