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<!DOCTYPE html>
<html lang="en-us">
<head>
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<meta name="author" content="Alexandre Ramé">
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<meta property="og:title" content="Alexandre Ramé">
<meta property="og:description" content="Deep learning scientist">
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<meta property="og:updated_time" content="2016-04-20T00:00:00+02:00">
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<title>Alexandre Ramé</title>
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<body id="top" data-spy="scroll" data-target="#navbar-main" data-offset="71" >
<nav class="navbar navbar-light fixed-top navbar-expand-lg py-0" id="navbar-main">
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<a class="nav-link" href="/#about" data-target="#about">
<span>Home</span>
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<a class="nav-link" href="/#publications" data-target="#publications">
<span>Publications</span>
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<a class="nav-link" href="/#talks_list" data-target="#talks_list">
<span>Talks/Posts</span>
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<a class="nav-link" href="/#teaching" data-target="#teaching">
<span>Teaching</span>
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<span>Books</span>
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<section id="about" class="home-section">
<div class="container">
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itemref="person-email person-telephone">
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<h2 itemprop="name">Alexandre Ramé</h2>
<h3 itemprop="jobTitle">Deep learning scientist</h3>
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<p>Research scientist at Google DeepMind, in Paris.
Post-training — distillation, RL, merging and reasoning — to improve the alignment of Gemma LLMs with the world in all its diversity.
My thesis received the 2024 SSFAM award of the best French PhD in ML.</p>
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<h3>Education</h3>
<ul class="ul-edu fa-ul">
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<p class="course">PhD in Deep Learning, 2020 - 2023</p>
<a href="https://www.isir.upmc.fr/">
<p class="institution">Sorbonne University (ISIR).</p>
</a>
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</li>
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<i class="fa-li fa fa-graduation-cap"></i>
<div class="description">
<p class="course">Master of Science in Applied Mathematics and Operations Research, 2014 - 2015</p>
<a href="https://www.columbia.edu/">
<p class="institution">Columbia University</p>
</a>
</div>
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<li>
<i class="fa-li fa fa-graduation-cap"></i>
<div class="description">
<p class="course">Diplôme d’ Ingénieur Polytechnicien, 2011 - 2014</p>
<a href="https://www.polytechnique.edu/en">
<p class="institution">Ecole Polytechnique</p>
</a>
</div>
</li>
</ul>
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<div class="col-sm-5">
<h3>Experience</h3>
<ul class="ul-edu fa-ul">
<li>
<i class="fa-li fa fa-briefcase"></i>
<div class="description">
<p class="course">Research Scientist, Mar 2024 - </p>
<a href="https://www.deepmind.com/">
<p class="institution">Google DeepMind</p>
</a>
</div>
</li>
<li>
<i class="fa-li fa fa-briefcase"></i>
<div class="description">
<p class="course">Student Researcher, Oct 2023 - Jan 2024</p>
<a href="https://www.deepmind.com/">
<p class="institution">Google DeepMind</p>
</a>
</div>
</li>
<li>
<i class="fa-li fa fa-briefcase"></i>
<div class="description">
<p class="course">Research Scientist Intern, Sep 2022 - Feb 2023</p>
<a href="https://ai.facebook.com/">
<p class="institution">FAIR Meta, Fairness and Robustness Team</p>
</a>
</div>
</li>
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<i class="fa-li fa fa-briefcase"></i>
<div class="description">
<p class="course">Research Scientist in Deep Learning, 2016 - 2020</p>
<a href="https://www.heuritech.com">
<p class="institution">Heuritech</p>
</a>
</div>
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</ul>
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</section>
<section id="publications" class="home-section">
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<h1>Selected Publications</h1>
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<a href="/publication/">
More Publications
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</p>
</div>
<div class="col-12 col-lg-8">
<div class="media stream-item" itemscope itemtype="http://schema.org/Event">
<div class="media-body">
<h3 class="article-title mb-0 mt-0" itemprop="name">
Gemma 3 Technical Report
</h3>
<div class="stream-meta article-metadata">
<div itemprop="author">
Gemma Team</div>
arXiv<br>
</div>
<div class="ml-3">
<img src="/publication/gemma3/featured_hu5c218cb7bdea72ee58992c9be91a8eb2_168064_400x0_resize_box_2.png" itemprop="image">
</div>
<div class="article-style" itemprop="articleBody">
We introduce Gemma 3, a multimodal addition to the Gemma family of lightweight open models, ranging in scale from 1 to 27 billion parameters. In particular, our novel post-training recipe significantly improves the math, chat, …
</div>
<div class="talk-links">
<a class="btn btn-primary btn-outline my-1 mr-1 btn-sm" href="https://arxiv.org/abs/2503.19786" target="_blank"
rel="noopener">
PDF
</a>
<button type="button" class="btn btn-primary btn-outline my-1 mr-1 btn-sm js-cite-modal"
data-filename="/publication/gemma3/cite.bib">
Cite
</button>
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</div>
<div class="media stream-item" itemscope itemtype="http://schema.org/Event">
<div class="media-body">
<h3 class="article-title mb-0 mt-0" itemprop="name">
On Teacher Hacking in Language Model Distillation
</h3>
<div class="stream-meta article-metadata">
<div itemprop="author">
Daniil Tiapkin, Daniele Calandriello, Johan Ferret, Sarah Perrin, Nino Vieillard, Alexandre Ramé, Mathieu Blondel</div>
arXiv<br>
</div>
<div class="ml-3">
</div>
<div class="article-style" itemprop="articleBody">
We study teacher hacking: does over-optimization of the distillation objective harm the ground-truth performance?
</div>
<div class="talk-links">
<a class="btn btn-primary btn-outline my-1 mr-1 btn-sm" href="https://arxiv.org/abs/2502.02671" target="_blank"
rel="noopener">
PDF
</a>
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data-filename="/publication/teacherhacking/cite.bib">
Cite
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<div class="media stream-item" itemscope itemtype="http://schema.org/Event">
<div class="media-body">
<h3 class="article-title mb-0 mt-0" itemprop="name">
Streaming DiLoCo with overlapping communication: Towards a Distributed Free Lunch
</h3>
<div class="stream-meta article-metadata">
<div itemprop="author">
Arthur Douillard, Yanislav Donchev, Keith Rush, Satyen Kale, Zachary Charles, Zachary Garrett, Gabriel Teston, Dave Lacey, Ross McIlroy, Jiajun Shen, Alexandre Ramé, Arthur Szlam, Marc’Aurelio Ranzato, Paul Barham</div>
arXiv<br>
</div>
<div class="ml-3">
</div>
<div class="article-style" itemprop="articleBody">
We improve DiLoCo in three ways. First, we synchronize only subsets of parameters in sequence. Second, we allow workers to continue training while synchronizing. Third, we quantize the data exchanged by workers.
</div>
<div class="talk-links">
<a class="btn btn-primary btn-outline my-1 mr-1 btn-sm" href="https://arxiv.org/abs/2501.18512" target="_blank"
rel="noopener">
PDF
</a>
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data-filename="/publication/streamingdiloco/cite.bib">
Cite
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<div class="media stream-item" itemscope itemtype="http://schema.org/Event">
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<h3 class="article-title mb-0 mt-0" itemprop="name">
Diversity-Rewarded CFG Distillation
</h3>
<div class="stream-meta article-metadata">
<div itemprop="author">
Geoffrey Cideron, Andrea Agostinelli, Johan Ferret, Sertan Girgin, Romuald Elie, Olivier Bachem, Sarah Perrin, Alexandre Ramé</div>
ICLR 2025<br>
</div>
<div class="ml-3">
</div>
<div class="article-style" itemprop="articleBody">
we introduce diversity-rewarded CFG distillation, a novel finetuning procedure that distills the strengths of CFG while addressing its limitations using RL and weight averaging.
</div>
<div class="talk-links">
<a class="btn btn-primary btn-outline my-1 mr-1 btn-sm" href="https://arxiv.org/abs/2410.06084" target="_blank"
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PDF
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<div class="media stream-item" itemscope itemtype="http://schema.org/Event">
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<h3 class="article-title mb-0 mt-0" itemprop="name">
Gemma 2: Improving Open Language Models at a Practical Size
</h3>
<div class="stream-meta article-metadata">
<div itemprop="author">
Gemma Team</div>
arXiv<br>
</div>
<div class="ml-3">
<img src="/publication/gemma2/featured_hua75fb1cb9281454f4a533c7f6e16493c_355818_400x0_resize_box_2.png" itemprop="image">
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We introduce Gemma 2, a new addition to the Gemma family of lightweight, state-of-the-art open models, ranging in scale from 2 billion to 27 billion parameter.
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WARP: On the Benefits of Weight Averaged Rewarded Policies
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<strong>Alexandre Ramé</strong>, Johan Ferret, Nino Vieillard, Robert Dadashi, Léonard Hussenot, Pierre-Louis Cedoz, Pier Giuseppe Sessa, Sertan Girgin, Arthur Douillard, Olivier Bachem</div>
arXiv<br>
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To improve the trade-off between KL and reward during RLHF, we leverage the ability to merge LLMs by weight averaging.
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WARM: On the Benefits of Weight Averaged Reward Models
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<strong>Alexandre Ramé</strong>, Nino Vieillard, Léonard Hussenot, Robert Dadashi, Geoffrey Cideron, Olivier Bachem, Johan Ferret</div>
ICML 2024<br>
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