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Charlotte Caucheteux
I am a Research Scientist in the LLaMa team at Meta (GenAI), working on fine-tuning Large Language Models.
My research interests include Large Language Models, Neuroscience, AI for healthcare & biology.
I graduated from Ecole Polytechnique in 2019 and pursed a PhD. in deep learning between 2020 and 2023 at Meta AI
(FAIR)
and Inria, focusing on representations in deep language models and the human brain.
Prior to my PhD, I gained experience in AI for Healthcare
as a data scientist at Owkin
and at the French Hospitals
AP-HP ,
where I contributed to a patient monitoring app during the COVID pandemic.
In 2019, I co-founded NoArtist, a collective of AI-generated artworks.
Feel free to connect on LinkedIn or Twitter .
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Selected Publications
I am interested in the computational basis of natural and artificial intelligence,
with a focus on language.
As part of my PhD., I have been investigating language representations in deep neural networks and the human brain,
using transformer-based language models and neuroimaging techniques (fMRI, MEG, and EEG).
My publication history can be found on Google Scholar .
Journal Articles
- Evidence of a predictive coding hierarchy in the human brain listening to speech
Charlotte Caucheteux, Alexandre Gramfort, Jean-Remi King.
Nature Human Behaviour, 2023
- Brains and algorithms partially converge in natural language processing
Charlotte Caucheteux , Jean-Remi King.
Nature Communications Biology, 2022
- Deep language algorithms predict semantic comprehension from brain activity
Charlotte Caucheteux, Alexandre Gramfort, Jean-Remi King.
Nature Scientific Reports , 2022
- Decoding speech from non-invasive brain recordings
Alexandre Defossez, Charlotte Caucheteux, Jeremy Rapin, Ori Kabeli, Jean-Remi King.
Forthcoming, Nature Machine Intelligence , 2022
- Predictive usefulness of RT-PCR testing in different patterns of Covid-19 symptomatology: analysis of a French cohort of 12,810 outpatients.
Caroline Apra*, Charlotte Caucheteux*, Arthur Mensch* et al.
, AP-HP/Universities/Inserm COVID-19 Research Collaboration.
Nature Scientific Reports, 2021
Conference Articles
- Toward a realistic model of speech processing in the brain with self-supervised learning
Juliette Millet*, Charlotte Caucheteux*, P. Orhan, Y. Boubenec, A. Gramfort, E. Dunbar, C. Pallier, J.R. King.
NeurIPS , 2022
- Disentangling syntax and semantics in the brain with deep networks
Charlotte Caucheteux, Alexandre Gramfort, Jean-Remi King.
ICML, 2021
- Model-based analysis of brain activity reveals the hierarchy of language in 305 subjects
Charlotte Caucheteux, Alexandre Gramfort, Jean-Remi King.
Findings of EMLNP , 2021
Press Coverage
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Misc.
- I received an MSc/BSc from Ecole Polytechnique (diplôme d'Ingénieur), with a specialisation in Machine Learning.
- I have a strong interest in Healthcare. Prior to my PhD., I had the chance to work for Owkin, a start-up (now unicorn!) applying AI to oncology (2017). I also worked for the Assistance Publique–Hôpitaux de Paris (AP-HP) during the COVID crisis (2019).
- Finally, I enjoy arts arts 🎨 and music 🎹. In 2019, two teammates and I founded NoArtist , a collective of AI-generated artworks. We regularly organise exhibitions and events to democratise AI through arts.
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