Paul Michel

According to our database, Paul Michel authored at least 26 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Language Evolution with Deep Learning.

Mathieu Rita, Paul Michel, Rahma Chaabouni, Olivier Pietquin, Emmanuel Dupoux, Florian Strub

CoRR, 2024

2023

Curriculum Learning with Adam: The Devil Is in the Wrong Details.

Lucas Weber, Jaap Jumelet, Paul Michel, Elia Bruni, Dieuwke Hupkes

CoRR, 2023

Neural Agents Struggle to Take Turns in Bidirectional Emergent Communication.

Valentin Taillandier, Dieuwke Hupkes, Benoît Sagot, Emmanuel Dupoux, Paul Michel

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Revisiting Populations in multi-agent Communication.

Paul Michel, Mathieu Rita, Kory Wallace Mathewson, Olivier Tieleman, Angeliki Lazaridou

Proceedings of the Eleventh International Conference on Learning Representations, 2023

AANG : Automating Auxiliary Learning.

Lucio M. Dery, Paul Michel, Mikhail Khodak, Graham Neubig, Ameet Talwalkar

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Emergent Communication: Generalization and Overfitting in Lewis Games.

Mathieu Rita, Corentin Tallec, Paul Michel, Jean-Bastien Grill, Olivier Pietquin, Emmanuel Dupoux, Florian Strub

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Distributionally Robust Models with Parametric Likelihood Ratios.

Paul Michel, Tatsunori Hashimoto, Graham Neubig

Proceedings of the Tenth International Conference on Learning Representations, 2022

Should We Be Pre-training? An Argument for End-task Aware Training as an Alternative.

Lucio M. Dery, Paul Michel, Ameet Talwalkar, Graham Neubig

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Balancing Average and Worst-case Accuracy in Multitask Learning.

Paul Michel, Sebastian Ruder, Dani Yogatama

CoRR, 2021

Learning Neural Models for Natural Language Processing in the Face of Distributional Shift.

Paul Michel

CoRR, 2021

Examining and Combating Spurious Features under Distribution Shift.

Chunting Zhou, Xuezhe Ma, Paul Michel, Graham Neubig

Proceedings of the 38th International Conference on Machine Learning, 2021

Modeling the Second Player in Distributionally Robust Optimization.

Paul Michel, Tatsunori Hashimoto, Graham Neubig

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Weight Poisoning Attacks on Pre-trained Models.

Keita Kurita, Paul Michel, Graham Neubig

CoRR, 2020

Findings of the WMT 2020 Shared Task on Machine Translation Robustness.

Lucia Specia, Zhenhao Li, Juan Miguel Pino, Vishrav Chaudhary, Francisco Guzmán, Graham Neubig, Nadir Durrani, Yonatan Belinkov, Philipp Koehn, Hassan Sajjad, Paul Michel, Xian Li

Proceedings of the Fifth Conference on Machine Translation, 2020

Optimizing Data Usage via Differentiable Rewards.

Xinyi Wang, Hieu Pham, Paul Michel, Antonios Anastasopoulos, Jaime G. Carbonell, Graham Neubig

Proceedings of the 37th International Conference on Machine Learning, 2020

Weight Poisoning Attacks on Pretrained Models.

Keita Kurita, Paul Michel, Graham Neubig

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019

Findings of the First Shared Task on Machine Translation Robustness.

Xian Li, Paul Michel, Antonios Anastasopoulos, Yonatan Belinkov, Nadir Durrani, Orhan Firat, Philipp Koehn, Graham Neubig, Juan Miguel Pino, Hassan Sajjad

Proceedings of the Fourth Conference on Machine Translation, 2019

Are Sixteen Heads Really Better than One?

Paul Michel, Omer Levy, Graham Neubig

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

compare-mt: A Tool for Holistic Comparison of Language Generation Systems.

Graham Neubig, Zi-Yi Dou, Junjie Hu, Paul Michel, Danish Pruthi, Xinyi Wang

Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019

On Evaluation of Adversarial Perturbations for Sequence-to-Sequence Models.

Paul Michel, Xian Li, Graham Neubig, Juan Miguel Pino

Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019

2018

MTNT: A Testbed for Machine Translation of Noisy Text.

Paul Michel, Graham Neubig

Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

Extreme Adaptation for Personalized Neural Machine Translation.

Paul Michel, Graham Neubig

Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, 2018

2017

DyNet: The Dynamic Neural Network Toolkit.

Graham Neubig, Chris Dyer, Yoav Goldberg, Austin Matthews, Waleed Ammar, Antonios Anastasopoulos, Miguel Ballesteros, David Chiang, Daniel Clothiaux, Trevor Cohn, Kevin Duh, Manaal Faruqui, Cynthia Gan, Dan Garrette, Yangfeng Ji, Lingpeng Kong, Adhiguna Kuncoro, Gaurav Kumar, Chaitanya Malaviya, Paul Michel, Yusuke Oda, Matthew Richardson, Naomi Saphra, Swabha Swayamdipta, Pengcheng Yin

CoRR, 2017

Does the Geometry of Word Embeddings Help Document Classification? A Case Study on Persistent Homology-Based Representations.

Paul Michel, Abhilasha Ravichander, Shruti Rijhwani

Proceedings of the 2nd Workshop on Representation Learning for NLP, 2017

Blind Phoneme Segmentation With Temporal Prediction Errors.

Paul Michel, Okko Räsänen, Roland Thiollière, Emmanuel Dupoux

Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, 2017

2016

Improving Phoneme segmentation with Recurrent Neural Networks.

Paul Michel, Okko Räsänen, Roland Thiollière, Emmanuel Dupoux

CoRR, 2016