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D-Index & Metrics

Computer Science

D-Index
30
Citations
18505
World Ranking
13804
National Ranking
5477

Overview

Alexis Conneau is a researcher affiliated with Facebook in the United States, specializing in computer science with a strong focus on artificial intelligence. Their research primarily addresses topics related to speech recognition and synthesis as well as natural language processing techniques.

Their recent publications demonstrate contributions to various aspects of speech and language technologies, including representation learning and few-shot learning evaluations. Notable papers include:

  • "XLS-R: Self-supervised Cross-lingual Speech Representation Learning at Scale," 2022, Interspeech 2022
  • "Supervised Contrastive Learning for Pre-trained Language Model Fine-tuning," 2020, arXiv (Cornell University)
  • "FLEURS: FEW-Shot Learning Evaluation of Universal Representations of Speech," 2023, 2022 IEEE Spoken Language Technology Workshop (SLT)
  • "Scaling Speech Technology to 1,000+ Languages," 2023, arXiv (Cornell University)
  • "GPT-4o System Card," 2024, arXiv (Cornell University)

Alexis Conneau frequently collaborates with several other researchers, including Michael Auli, Alexei Baevski, Ankur Bapna, Andros Tjandra, and Jason Riesa. These collaborations have led to numerous joint publications that span multiple venues.

Their work has appeared extensively in publication venues such as:

  • arXiv (Cornell University), with 20 publications
  • Interspeech 2022, with 3 publications
  • 2022 IEEE Spoken Language Technology Workshop (SLT), with 1 publication
  • ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), with 1 publication

The main fields of study for Alexis Conneau include computer science, with specialized research in artificial intelligence, signal processing, and computer vision and pattern recognition. Their work covers significant subfields and topics such as:

  • Artificial Intelligence
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Speech Recognition and Synthesis
  • Natural Language Processing Techniques
  • Topic Modeling
  • Music and Audio Processing
  • Multimodal Machine Learning Applications
  • Domain Adaptation and Few-Shot Learning
  • Speech and Audio Processing

Best Publications

  • Unsupervised Cross-lingual Representation Learning at Scale

    Alexis Conneau;Kartikay Khandelwal;Naman Goyal;Vishrav Chaudhary

  • Supervised learning of universal sentence representations from natural language inference data

    Alexis Conneau;Douwe Kiela;Holger Schwenk;Loïc Barrault

  • Cross-lingual Language Model Pretraining

    Alexis Conneau;Guillaume Lample

  • Word translation without parallel data

    Guillaume Lample;Alexis Conneau;Marc'Aurelio Ranzato;Ludovic Denoyer

  • Very deep convolutional networks for text classification

    Alexis Conneau;Holger Schwenk;Loïc Barrault;Yann Lecun

  • XNLI: Evaluating Cross-lingual Sentence Representations

    Alexis Conneau;Ruty Rinott;Guillaume Lample;Adina Williams

  • What you can cram into a single \$&!#* vector: Probing sentence embeddings for linguistic properties

    Alexis Conneau;German Kruszewski;Guillaume Lample;Loïc Barrault

  • Phrase-Based & Neural Unsupervised Machine Translation

    Guillaume Lample;Myle Ott;Alexis Conneau;Ludovic Denoyer

  • Unsupervised Machine Translation Using Monolingual Corpora Only

    Guillaume Lample;Alexis Conneau;Ludovic Denoyer;Marc'Aurelio Ranzato

  • Unsupervised Cross-lingual Representation Learning for Speech Recognition

    Alexis Conneau;Alexei Baevski;Ronan Collobert;Abdelrahman Mohamed

  • SentEval: An Evaluation Toolkit for Universal Sentence Representations

    Alexis Conneau;Douwe Kiela

  • XLS-R: Self-supervised Cross-lingual Speech Representation Learning at Scale

    Arun Babu;Changhan Wang;Andros Tjandra;Kushal Lakhotia

  • Word Translation Without Parallel Data

    Alexis Conneau;Guillaume Lample;Marc'Aurelio Ranzato;Ludovic Denoyer

  • CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data

    Guillaume Wenzek;Marie-Anne Lachaux;Alexis Conneau;Vishrav Chaudhary

  • Very Deep Convolutional Networks for Natural Language Processing.

    Alexis Conneau;Holger Schwenk;Loïc Barrault;Yann LeCun

  • Meta-Prod2Vec: Product Embeddings Using Side-Information for Recommendation

    Flavian Vasile;Elena Smirnova;Alexis Conneau

  • XNLI: Evaluating Cross-lingual Sentence Representations

    Alexis Conneau;Guillaume Lample;Ruty Rinott;Adina Williams

  • Emerging Cross-lingual Structure in Pretrained Language Models

    Alexis Conneau;Shijie Wu;Haoran Li;Luke Zettlemoyer

  • FLEURS: FEW-Shot Learning Evaluation of Universal Representations of Speech

    Unknown

  • Unsupervised Machine Translation Using Monolingual Corpora Only

    Guillaume Lample;Alexis Conneau;Ludovic Denoyer;Marc'Aurelio Ranzato

  • Self-training Improves Pre-training for Natural Language Understanding

    Jingfei Du;Edouard Grave;Beliz Gunel;Vishrav Chaudhary

  • Emerging Cross-lingual Structure in Pretrained Language Models

    Shijie Wu;Alexis Conneau;Haoran Li;Luke Zettlemoyer

Frequent Co-Authors

Michael Auli
Michael Auli Facebook (United States)
Veselin Stoyanov
Veselin Stoyanov Facebook (United States)
Holger Schwenk
Holger Schwenk Facebook (United States)
Myle Ott
Myle Ott Facebook (United States)
Douwe Kiela
Douwe Kiela Stanford University
Edouard Grave
Edouard Grave Facebook (United States)
Marc'Aurelio Ranzato
Marc'Aurelio Ranzato DeepMind (United Kingdom)
Ludovic Denoyer
Ludovic Denoyer Sorbonne University
Luke Zettlemoyer
Luke Zettlemoyer University of Washington
Ronan Collobert
Ronan Collobert Facebook (United States)

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