David Grangier

13.2k citations
43 papers · 4.7k indexed · 5 hit papers · h-index 18

David Grangier

39 papers receiving 4.3k citations

Hit Papers

AudioLM: A Language Modelin...20120172026202020234008001.2k

Peers

David Grangier
Comparison fields: 5 of 118
  • Artificial Intelligence 3.9k
  • Computer Vision and Pattern Recognition 1.8k
  • Signal Processing 605
  • Health Informatics 18
  • Information Systems 281
Replace Yann Dauphin with:
Yann Dauphin United States
Michael Auli United States
Phil Blunsom United Kingdom
Dilek Hakkani‐Tür United States
Qun Liu China
Matthieu Devin United States
Serhii Havrylov Ukraine
Shiyu Chang United States
Frank Seide China
Zhe Gan United States
David Grangier relative to Yann Dauphin United States Yann Dauphin's profile →
Citations per field
00.5×1.5×2.5×
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-authorship network

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
#Work
1 20244
2
AudioLM: A Language Modeling Approach to Audio Generationbreakdown →
2023201
3 2021145
4 20200
5
fairseq: A Fast, Extensible Toolkit for Sequence Modelingbreakdown →
20191381
6
Understanding Back-Translation at Scalebreakdown →
2018539
7
QuaterNet: A Quaternion-based Recurrent Model for Human Motion.
201828
8
Convolutional Sequence to Sequence Learningbreakdown →
2017666
9
Language modeling with gated convolutional networksbreakdown →
2017454
10
QuickEdit: Editing Text & Translations via Simple Delete Actions.
20175
11 201640
12
Label Embedding Trees for Large Multi-Class Tasks
2010177
13 200985
14 200960
15 2008238
16
Discriminative Keyword Spotting
20074
17
A Neural Network to Retrieve Images from Text Queries
20061
18
Exploiting Hyperlinks to Learn a Retrieval Model
20055
19 200512
20
Information Retrieval on Noisy Text
20036

About David Grangier

David Grangier is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing, Information Systems and Media Technology, having authored 43 papers that have together received 4.7k indexed citations. Recurring topics across this work include Topic Modeling (21 papers), Natural Language Processing Techniques (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 (605 citations), Health Informatics (18 citations) and Information Systems (281 citations). David Grangier has collaborated with scholars based in United States, Switzerland and Israel. Frequent co-authors include Michael Auli, Yann Dauphin, Myle Ott, Sergey Edunov, Angela Fan, Samy Bengio, Jonas Gehring, Sam Gross, Nathan Ng and Alexei Baevski. Their work appears in journals such as Transactions of the Association for Computational Linguistics, Speech Communication, IEEE Transactions on Pattern Analysis and Machine Intelligence, Statistical Analysis and Data Mining The ASA Data Science Journal and IEEE/ACM Transactions on Audio Speech and Language Processing.

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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