Improving Phoneme segmentation with Recurrent Neural Networks. - Paul Michel; Okko Räsänen; Roland Thiollière; Emmanuel Dupoux (CoRR, 2016)

Blind Phoneme Segmentation With Temporal Prediction Errors. - Paul Michel; Okko Räsänen; Roland Thiollière; Emmanuel Dupoux (ACL (Student Research Workshop), 2017)

Does the Geometry of Word Embeddings Help Document Classification? A Case Study on Persistent Homology-Based Representations. - Paul Michel; Abhilasha Ravichander; Shruti Rijhwani (Rep4NLP@ACL, 2017)

DyNet: The Dynamic Neural Network Toolkit. - Graham Neubig; Chris Dyer; Yoav Goldberg; Austin Matthews; Waleed Ammar; Antonios Anastasopoulos; Miguel Ballesteros; David Chiang 001; Daniel Clothiaux; Trevor Cohn; Kevin Duh; Manaal Faruqui; et al. (CoRR, 2017)

Extreme Adaptation for Personalized Neural Machine Translation. - Paul Michel; Graham Neubig (ACL (2), 2018)

MTNT: A Testbed for Machine Translation of Noisy Text. - Paul Michel; Graham Neubig (EMNLP, 2018)

On Evaluation of Adversarial Perturbations for Sequence-to-Sequence Models. - Paul Michel; Xian Li 003; Graham Neubig; Juan Miguel Pino (NAACL-HLT (1), 2019)

compare-mt: A Tool for Holistic Comparison of Language Generation Systems. - Graham Neubig; Zi-Yi Dou; Junjie Hu 001; Paul Michel; Danish Pruthi; Xinyi Wang 001 (NAACL-HLT (Demonstrations), 2019)

Are Sixteen Heads Really Better than One? - Paul Michel; Omer Levy; Graham Neubig (NeurIPS, 2019)

Findings of the First Shared Task on Machine Translation Robustness. - Xian Li 003; Paul Michel; Antonios Anastasopoulos; Yonatan Belinkov; Nadir Durrani; Orhan Firat; Philipp Koehn; Graham Neubig; Juan Miguel Pino; Hassan Sajjad 001 (WMT (2), 2019)

Weight Poisoning Attacks on Pretrained Models. - Keita Kurita; Paul Michel; Graham Neubig (ACL, 2020)

Optimizing Data Usage via Differentiable Rewards. - Xinyi Wang 001; Hieu Pham; Paul Michel; Antonios Anastasopoulos; Jaime G. Carbonell; Graham Neubig (ICML, 2020)

Findings of the WMT 2020 Shared Task on Machine Translation Robustness. - Lucia Specia; Zhenhao Li 003; Juan Miguel Pino; Vishrav Chaudhary; Francisco Guzmán; Graham Neubig; Nadir Durrani; Yonatan Belinkov; Philipp Koehn; Hassan Sajjad 001; Paul Michel; Xian Li 003 (WMT@EMNLP, 2020)

Weight Poisoning Attacks on Pre-trained Models. - Keita Kurita; Paul Michel; Graham Neubig (CoRR, 2020)

Modeling the Second Player in Distributionally Robust Optimization. - Paul Michel; Tatsunori Hashimoto; Graham Neubig (ICLR, 2021)

Examining and Combating Spurious Features under Distribution Shift. - Chunting Zhou; Xuezhe Ma; Paul Michel; Graham Neubig (ICML, 2021)

Learning Neural Models for Natural Language Processing in the Face of Distributional Shift. - Paul Michel (CoRR, 2021)

Balancing Average and Worst-case Accuracy in Multitask Learning. - Paul Michel; Sebastian Ruder; Dani Yogatama (CoRR, 2021)

Should We Be Pre-training? An Argument for End-task Aware Training as an Alternative. - Lucio M. Dery; Paul Michel; Ameet Talwalkar; Graham Neubig (ICLR, 2022)

Distributionally Robust Models with Parametric Likelihood Ratios. - Paul Michel; Tatsunori Hashimoto; Graham Neubig (ICLR, 2022)

Emergent Communication: Generalization and Overfitting in Lewis Games. - Mathieu Rita; Corentin Tallec; Paul Michel; Jean-Bastien Grill; Olivier Pietquin; Emmanuel Dupoux; Florian Strub (NeurIPS, 2022)

AANG : Automating Auxiliary Learning. - Lucio M. Dery; Paul Michel; Mikhail Khodak; Graham Neubig; Ameet Talwalkar (ICLR, 2023)

Revisiting Populations in multi-agent Communication. - Paul Michel; Mathieu Rita; Kory Wallace Mathewson; Olivier Tieleman; Angeliki Lazaridou (ICLR, 2023)

Neural Agents Struggle to Take Turns in Bidirectional Emergent Communication. - Valentin Taillandier; Dieuwke Hupkes; Benoît Sagot; Emmanuel Dupoux; Paul Michel (ICLR, 2023)

Curriculum Learning with Adam: The Devil Is in the Wrong Details. - Lucas Weber; Jaap Jumelet; Paul Michel; Elia Bruni; Dieuwke Hupkes (CoRR, 2023)

Countering Reward Over-Optimization in LLM with Demonstration-Guided Reinforcement Learning. - Mathieu Rita; Florian Strub; Rahma Chaabouni 001; Paul Michel; Emmanuel Dupoux; Olivier Pietquin (ACL (Findings), 2024)

Language Evolution with Deep Learning. - Mathieu Rita; Paul Michel; Rahma Chaabouni 001; Olivier Pietquin; Emmanuel Dupoux; Florian Strub (CoRR, 2024)

CodeGemma: Open Code Models Based on Gemma. - Heri Zhao; Jeffrey Hui; Joshua Howland; Nam Nguyen; Siqi Zuo; Andrea Hu; Christopher A. Choquette-Choo; Jingyue Shen; Joe Kelley; Kshitij Bansal; Luke Vilnis; Mateo Wirth; et al. (CoRR, 2024)