Leveraging Weakly Annotated Data for Fashion Image Retrieval and Label Prediction. - Charles Corbière; Hédi Ben-Younes; Alexandre Ramé; Charles Ollion (ICCV Workshops, 2017)

OMNIA Faster R-CNN: Detection in the wild through dataset merging and soft distillation. - Alexandre Ramé; Emilien Garreau; Hedi Ben-Younes; Charles Ollion (CoRR, 2018)

CORE: Color Regression for Multiple Colors Fashion Garments. - Alexandre Ramé; Arthur Douillard; Charles Ollion (CoRR, 2020)

MixMo: Mixing Multiple Inputs for Multiple Outputs via Deep Subnetworks. - Alexandre Ramé; Rémy Sun; Matthieu Cord (ICCV, 2021)

DICE: Diversity in Deep Ensembles via Conditional Redundancy Adversarial Estimation. - Alexandre Ramé; Matthieu Cord (ICLR, 2021)

DyTox: Transformers for Continual Learning with DYnamic TOken eXpansion. - Arthur Douillard; Alexandre Ramé; Guillaume Couairon; Matthieu Cord (CVPR, 2022)

CoRe: Color Regression for Multicolor Fashion Garments. - Alexandre Ramé; Arthur Douillard; Charles Ollion (CVPR Workshops, 2022)

Towards efficient feature sharing in MIMO architectures. - Rémy Sun; Alexandre Ramé; Clément Masson; Nicolas Thome; Matthieu Cord (CVPR Workshops, 2022)

Fishr: Invariant Gradient Variances for Out-of-Distribution Generalization. - Alexandre Ramé; Corentin Dancette; Matthieu Cord (ICML, 2022)

Diverse Weight Averaging for Out-of-Distribution Generalization. - Alexandre Ramé; Matthieu Kirchmeyer; Thibaud Rahier; Alain Rakotomamonjy; Patrick Gallinari; Matthieu Cord (NeurIPS, 2022)

Recycling diverse models for out-of-distribution generalization. - Alexandre Ramé; Kartik Ahuja; Jianyu Zhang; Matthieu Cord; Léon Bottou; David Lopez-Paz (CoRR, 2022)

Model Ratatouille: Recycling Diverse Models for Out-of-Distribution Generalization. - Alexandre Ramé; Kartik Ahuja; Jianyu Zhang; Matthieu Cord; Léon Bottou; David Lopez-Paz (ICML, 2023)

Rewarded soups: towards Pareto-optimal alignment by interpolating weights fine-tuned on diverse rewards. - Alexandre Ramé; Guillaume Couairon; Corentin Dancette; Jean-Baptiste Gaya; Mustafa Shukor; Laure Soulier; Matthieu Cord (NeurIPS, 2023)

Unified Model for Image, Video, Audio and Language Tasks. - Mustafa Shukor; Corentin Dancette; Alexandre Ramé; Matthieu Cord (CoRR, 2023)

UnIVAL: Unified Model for Image, Video, Audio and Language Tasks. - Mustafa Shukor; Corentin Dancette; Alexandre Ramé; Matthieu Cord (Trans. Mach. Learn. Res., 2023)

Diverse and efficient ensembling of deep networks. (De la diversification et combinaison efficace des réseaux profonds). - Alexandre Ramé (2023)

Conditional Language Policy: A General Framework For Steerable Multi-Objective Finetuning. - Kaiwen Wang; Rahul Kidambi; Ryan Sullivan; Alekh Agarwal; Christoph Dann; Andrea Michi; Marco Gelmi; Yunxuan Li; Raghav Gupta; Avinava Dubey; Alexandre Ramé; Johan Ferret; et al. (EMNLP (Findings), 2024)

Beyond task performance: evaluating and reducing the flaws of large multimodal models with in-context-learning. - Mustafa Shukor; Alexandre Ramé; Corentin Dancette; Matthieu Cord (ICLR, 2024)

WARM: On the Benefits of Weight Averaged Reward Models. - Alexandre Ramé; Nino Vieillard; Léonard Hussenot; Robert Dadashi; Geoffrey Cideron; Olivier Bachem; Johan Ferret (ICML, 2024)

Direct Language Model Alignment from Online AI Feedback. - Shangmin Guo; Biao Zhang; Tianlin Liu; Tianqi Liu 002; Misha Khalman; Felipe Llinares; Alexandre Ramé; Thomas Mesnard; Yao Zhao; Bilal Piot; Johan Ferret; Mathieu Blondel (CoRR, 2024)

WARP: On the Benefits of Weight Averaged Rewarded Policies. - Alexandre Ramé; Johan Ferret; Nino Vieillard; Robert Dadashi; Léonard Hussenot; Pierre-Louis Cedoz; Pier Giuseppe Sessa; Sertan Girgin; Arthur Douillard; Olivier Bachem (CoRR, 2024)

BOND: Aligning LLMs with Best-of-N Distillation. - Pier Giuseppe Sessa; Robert Dadashi; Léonard Hussenot; Johan Ferret; Nino Vieillard; Alexandre Ramé; Bobak Shahriari; Sarah Perrin; Abe Friesen; Geoffrey Cideron; Sertan Girgin; Piotr Stanczyk; et al. (CoRR, 2024)

Conditioned Language Policy: A General Framework for Steerable Multi-Objective Finetuning. - Kaiwen Wang; Rahul Kidambi; Ryan Sullivan; Alekh Agarwal; Christoph Dann; Andrea Michi; Marco Gelmi; Yunxuan Li; Raghav Gupta; Avinava Dubey; Alexandre Ramé; Johan Ferret; et al. (CoRR, 2024)

Gemma 2: Improving Open Language Models at a Practical Size. - Morgane Rivière; Shreya Pathak; Pier Giuseppe Sessa; Cassidy Hardin; Surya Bhupatiraju; Léonard Hussenot; Thomas Mesnard; Bobak Shahriari; Alexandre Ramé; Johan Ferret; Peter Liu; Pouya Tafti; et al. (CoRR, 2024)

Diversity-Rewarded CFG Distillation. - Geoffrey Cideron; Andrea Agostinelli; Johan Ferret; Sertan Girgin; Romuald Elie; Olivier Bachem; Sarah Perrin; Alexandre Ramé (ICLR, 2025)

BOND: Aligning LLMs with Best-of-N Distillation. - Pier Giuseppe Sessa; Robert Dadashi-Tazehozi; Léonard Hussenot; Johan Ferret; Nino Vieillard; Alexandre Ramé; Bobak Shahriari; Sarah Perrin; Abram L. Friesen; Geoffrey Cideron; Sertan Girgin; Piotr Stanczyk; et al. (ICLR, 2025)

Streaming DiLoCo with overlapping communication: Towards a Distributed Free Lunch. - Arthur Douillard; Yanislav Donchev; Keith Rush; Satyen Kale; Zachary Charles; Zachary Garrett; Gabriel Teston; Dave Lacey; Ross McIlroy; Jiajun Shen; Alexandre Ramé; Arthur Szlam; et al. (CoRR, 2025)

On Teacher Hacking in Language Model Distillation. - Daniil Tiapkin; Daniele Calandriello; Johan Ferret; Sarah Perrin; Nino Vieillard; Alexandre Ramé; Mathieu Blondel (CoRR, 2025)

Gemma 3 Technical Report. - Aishwarya Kamath; Johan Ferret; Shreya Pathak; Nino Vieillard; Ramona Merhej; Sarah Perrin; Tatiana Matejovicova; Alexandre Ramé; Morgane Rivière; Louis Rouillard; Thomas Mesnard; Geoffrey Cideron; et al. (CoRR, 2025)

MedGemma Technical Report. - Andrew Sellergren; Sahar Kazemzadeh; Tiam Jaroensri; Atilla P. Kiraly; Madeleine Traverse; Timo Kohlberger; Shawn Xu; Fayaz Jamil; Cían Hughes; Charles Lau; Justin Chen; Fereshteh Mahvar; et al. (CoRR, 2025)

Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities. - Gheorghe Comanici; Eric Bieber; Mike Schaekermann; Ice Pasupat; Noveen Sachdeva; Inderjit S. Dhillon; Marcel Blistein; Ori Ram; Dan Zhang; Evan Rosen; Luke Marris; Sam Petulla; et al. (CoRR, 2025)