David Grangier

13.4k citations
43 papers · 4.8k · 5 hit papers · h-index 18

Impact in

Papers in

David Grangier

39 papers receiving 4.4k citations

David Grangier's Hit Papers

AudioLM: A Language Modeling Approach to Audio Generation 2023 · 225 citations
2250+3+6Years since publication4008001.2k

Peers

David Grangier
Comparison fields: 5 of 118
  • Artificial Intelligence 3.9k
  • Computer Vision and Pattern Recognition 1.8k
  • Signal Processing 621
  • Information Systems 280
  • Computational Mathematics 7
Replace Yann Dauphin with:
Yann Dauphin United States
Michael Auli United States
Yasemin Altün United States
Phil Blunsom United Kingdom
Andrew L. Maas United States
Dilek Hakkani‐Tür United States
Serhii Havrylov Ukraine
Matthieu Devin United States
Ioannis Tsochantaridis United States
Zhe Gan United States
David Grangier relative to Yann Dauphin United States Yann Dauphin's profile →
Citations per field
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Yann Dauphin · 1×
Citations per year

Countries citing papers authored by David Grangier

Since Specialization
Citations

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

Fields of papers citing papers by David Grangier

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside David Grangier, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with David Grangier Line = papers co-authored together David Grangier links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 43 papers — load more, or switch the sort, to bring in the rest.

#Work
1
fairseq: A Fast, Extensible Toolkit for Sequence Modeling
Hit paper breakdown →
20191410
2
Convolutional Sequence to Sequence Learning
Hit paper breakdown →
2017666
3
Understanding Back-Translation at Scale
Hit paper breakdown →
2018551
4
Language modeling with gated convolutional networks
Hit paper breakdown →
2017455
5 2017270
6 2008238
7
AudioLM: A Language Modeling Approach to Audio Generation
Hit paper breakdown →
2023225
8
Label Embedding Trees for Large Multi-Class Tasks
2010178
9 2021149
10 2018149
11 200985
12 200878
13 200960
14 201642
15
Polynomial Semantic Indexing
200935
16
QuaterNet: A Quaternion-based Recurrent Model for Human Motion.
201828
17 201924
18 202218
19 201214
20 200512

About David Grangier

David Grangier is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing, Information Systems and Control and Systems Engineering, having authored 43 papers that have together received 4.8k indexed citations. Recurring topics across this work include Natural Language Processing Techniques (21 papers), Topic Modeling (21 papers), Speech Recognition and Synthesis (9 papers), Multimodal Machine Learning Applications (8 papers), Text and Document Classification Technologies (8 papers), Music and Audio Processing (6 papers), Advanced Image and Video Retrieval Techniques (6 papers) and Speech and Audio Processing (5 papers). The work is most often cited by research in Artificial Intelligence (3.9k citations), Computer Vision and Pattern Recognition (1.8k citations), Signal Processing (621 citations), Information Systems (280 citations) and Computational Mathematics (7 citations). David Grangier has collaborated with scholars based in United States, Switzerland and Israel. Frequent co-authors include Michael Auli, Yann Dauphin, Sergey Edunov, Myle Ott, Angela Fan, Samy Bengio, Jonas Gehring, Sam Gross, Alexei Baevski and Nathan Ng. Their work appears in journals such as Transactions of the Association for Computational Linguistics, Speech Communication, IEEE/ACM Transactions on Audio Speech and Language Processing, Information Retrieval and Statistical Analysis and Data Mining The ASA Data Science Journal.

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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