Olivier Delalleau

According to our database, Olivier Delalleau authored at least 35 papers between 2003 and 2025.

Collaborative distances:

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

2025

HelpSteer3-Preference: Open Human-Annotated Preference Data across Diverse Tasks and Languages.

Zhilin Wang, Jiaqi Zeng, Olivier Delalleau, Hoo-Chang Shin, Felipe Soares, Alexander Bukharin, Ellie Evans, Yi Dong, Oleksii Kuchaiev

CoRR, May, 2025

Llama-Nemotron: Efficient Reasoning Models.

Akhiad Bercovich, Itay Levy, Izik Golan, Mohammad Dabbah, Ran El-Yaniv, Omri Puny, Ido Galil, Zach Moshe, Tomer Ronen, Najeeb Nabwani, Ido Shahaf, Oren Tropp, Ehud Karpas, Ran Zilberstein, Jiaqi Zeng, Soumye Singhal, Alexander Bukharin, Yian Zhang, Tugrul Konuk, Gerald Shen, Ameya Sunil Mahabaleshwarkar, Bilal Kartal, Yoshi Suhara, Olivier Delalleau, Zijia Chen, Zhilin Wang, David Mosallanezhad, Adi Renduchintala, Haifeng Qian, Dima Rekesh, Fei Jia, Somshubra Majumdar, Vahid Noroozi, Wasi Uddin Ahmad, Sean Narenthiran, Aleksander Ficek, Mehrzad Samadi, Jocelyn Huang, Siddhartha Jain, Igor Gitman, Ivan Moshkov, Wei Du, Shubham Toshniwal, George Armstrong, Branislav Kisacanin, Matvei Novikov, Daria Gitman, Evelina Bakhturina, Jane Polak Scowcroft, John Kamalu, Dan Su, Kezhi Kong, Markus Kliegl, Rabeeh Karimi, Ying Lin, Sanjeev Satheesh, Jupinder Parmar, Pritam Gundecha, Brandon Norick, Joseph Jennings, Shrimai Prabhumoye, Syeda Nahida Akter, Mostofa Patwary, Abhinav Khattar, Deepak Narayanan, Roger Waleffe, Jimmy Zhang, Bor-Yiing Su, Guyue Huang, Terry Kong, Parth Chadha, Sahil Jain, Christine Harvey, Elad Segal, Jining Huang, Sergey Kashirsky, Robert McQueen, Izzy Putterman, George Lam, Arun Venkatesan, Sherry Wu, Vinh Nguyen, Manoj Kilaru, Andrew Wang, Anna Warno, Abhilash Somasamudramath, Sandip Bhaskar, Maka Dong, Nave Assaf, Shahar Mor, Omer Ullman Argov, Scot Junkin, Oleksandr Romanenko, Pedro Larroy, Monika Katariya, Marco Rovinelli, Viji Balas, Nicholas Edelman, Anahita Bhiwandiwalla, Muthu Subramaniam

CoRR, May, 2025

Adversarial Training of Reward Models.

Alexander Bukharin, Haifeng Qian, Shengyang Sun, Adithya Renduchintala, Soumye Singhal, Zhilin Wang, Oleksii Kuchaiev, Olivier Delalleau, Tuo Zhao

CoRR, April, 2025

Dedicated Feedback and Edit Models Empower Inference-Time Scaling for Open-Ended General-Domain Tasks.

Zhilin Wang, Jiaqi Zeng, Olivier Delalleau, Daniel Egert, Ellie Evans, Hoo-Chang Shin, Felipe Soares, Yi Dong, Oleksii Kuchaiev

CoRR, March, 2025

Reward-aware Preference Optimization: A Unified Mathematical Framework for Model Alignment.

Shengyang Sun, Yian Zhang, Alexander Bukharin, David Mosallanezhad, Jiaqi Zeng, Soumye Singhal, Gerald Shen, Adithya Renduchintala, Tugrul Konuk, Yi Dong, Zhilin Wang, Dmitry Chichkov, Olivier Delalleau, Oleksii Kuchaiev

CoRR, February, 2025

HelpSteer2-Preference: Complementing Ratings with Preferences.

Zhilin Wang, Alexander Bukharin, Olivier Delalleau, Daniel Egert, Gerald Shen, Jiaqi Zeng, Oleksii Kuchaiev, Yi Dong

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

HelpSteer3: Human-Annotated Feedback and Edit Data to Empower Inference-Time Scaling in Open-Ended General-Domain Tasks.

Zhilin Wang, Jiaqi Zeng, Olivier Delalleau, Daniel Egert, Ellie Evans, Hoo-Chang Shin, Felipe Soares, Yi Dong, Oleksii Kuchaiev

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

2024

Diverging Preferences: When do Annotators Disagree and do Models Know?

Michael J. Q. Zhang, Zhilin Wang, Jena D. Hwang, Yi Dong, Olivier Delalleau, Yejin Choi, Eunsol Choi, Xiang Ren, Valentina Pyatkin

CoRR, 2024

Nemotron-4 340B Technical Report.

Bo Adler, Niket Agarwal, Ashwath Aithal, Dong H. Anh, Pallab Bhattacharya, Annika Brundyn, Jared Casper, Bryan Catanzaro, Sharon Clay, Jonathan M. Cohen, Sirshak Das, Ayush Dattagupta, Olivier Delalleau, Leon Derczynski, Yi Dong, Daniel Egert, Ellie Evans, Aleksander Ficek, Denys Fridman, Shaona Ghosh, Boris Ginsburg, Igor Gitman, Tomasz Grzegorzek, Robert Hero, Jining Huang, Vibhu Jawa, Joseph Jennings, Aastha Jhunjhunwala, John Kamalu, Sadaf Khan, Oleksii Kuchaiev, Patrick LeGresley, Hui Li, Jiwei Liu, Zihan Liu, Eileen Long, Ameya Sunil Mahabaleshwarkar, Somshubra Majumdar, James Maki, Miguel Martinez, Maer Rodrigues de Melo, Ivan Moshkov, Deepak Narayanan, Sean Narenthiran, Jesus Navarro, Phong Nguyen, Osvald Nitski, Vahid Noroozi, Guruprasad Nutheti, Christopher Parisien, Jupinder Parmar, Mostofa Patwary, Krzysztof Pawelec, Wei Ping, Shrimai Prabhumoye, Rajarshi Roy, Trisha Saar, Vasanth Rao Naik Sabavat, Sanjeev Satheesh, Jane Polak Scowcroft, Jason Sewall, Pavel Shamis, Gerald Shen, Mohammad Shoeybi, Dave Sizer, Misha Smelyanskiy, Felipe Soares, Makesh Narsimhan Sreedhar, Dan Su, Sandeep Subramanian, Shengyang Sun, Shubham Toshniwal, Hao Wang, Zhilin Wang, Jiaxuan You, Jiaqi Zeng, Jimmy Zhang, Jing Zhang, Vivienne Zhang, Yian Zhang, Chen Zhu

CoRR, 2024

HelpSteer2: Open-source dataset for training top-performing reward models.

Zhilin Wang, Yi Dong, Olivier Delalleau, Jiaqi Zeng, Gerald Shen, Daniel Egert, Jimmy J. Zhang, Makesh Narsimhan Sreedhar, Oleksii Kuchaiev

CoRR, 2024

NeMo-Aligner: Scalable Toolkit for Efficient Model Alignment.

Gerald Shen, Zhilin Wang, Olivier Delalleau, Jiaqi Zeng, Yi Dong, Daniel Egert, Shengyang Sun, Jimmy J. Zhang, Sahil Jain, Ali Taghibakhshi, Markel Sanz Ausin, Ashwath Aithal, Oleksii Kuchaiev

CoRR, 2024

HelpSteer 2: Open-source dataset for training top-performing reward models.

Zhilin Wang, Yi Dong, Olivier Delalleau, Jiaqi Zeng, Gerald Shen, Daniel Egert, Jimmy Zhang, Makesh Narsimhan Sreedhar, Oleksii Kuchaiev

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

HelpSteer: Multi-attribute Helpfulness Dataset for SteerLM.

Zhilin Wang, Yi Dong, Jiaqi Zeng, Virginia Adams, Makesh Narsimhan Sreedhar, Daniel Egert, Olivier Delalleau, Jane Polak Scowcroft, Neel Kant, Aidan Swope, Oleksii Kuchaiev

Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

IQL-TD-MPC: Implicit Q-Learning for Hierarchical Model Predictive Control.

Rohan Chitnis, Yingchen Xu, Bobak Hashemi, Lucas Lehnert, Ürün Dogan, Zheqing Zhu, Olivier Delalleau

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

2020

A Closer Look at Codistillation for Distributed Training.

Shagun Sodhani, Olivier Delalleau, Mahmoud Assran, Koustuv Sinha, Nicolas Ballas, Michael G. Rabbat

CoRR, 2020

2019

Discrete and Continuous Action Representation for Practical RL in Video Games.

Olivier Delalleau, Maxim Peter, Eloi Alonso, Adrien Logut

CoRR, 2019

2016

Theano: A Python framework for fast computation of mathematical expressions.

Rami Al-Rfou, Guillaume Alain, Amjad Almahairi, Christof Angermüller, Dzmitry Bahdanau, Nicolas Ballas, Frédéric Bastien, Justin Bayer, Anatoly Belikov, Alexander Belopolsky, Yoshua Bengio, Arnaud Bergeron, James Bergstra, Valentin Bisson, Josh Bleecher Snyder, Nicolas Bouchard, Nicolas Boulanger-Lewandowski, Xavier Bouthillier, Alexandre de Brébisson, Olivier Breuleux, Pierre Luc Carrier, Kyunghyun Cho, Jan Chorowski, Paul F. Christiano, Tim Cooijmans, Marc-Alexandre Côté, Myriam Côté, Aaron C. Courville, Yann N. Dauphin, Olivier Delalleau, Julien Demouth, Guillaume Desjardins, Sander Dieleman, Laurent Dinh, Melanie Ducoffe, Vincent Dumoulin, Samira Ebrahimi Kahou, Dumitru Erhan, Ziye Fan, Orhan Firat, Mathieu Germain, Xavier Glorot, Ian J. Goodfellow, Matthew Graham, Çaglar Gülçehre, Philippe Hamel, Iban Harlouchet, Jean-Philippe Heng, Balázs Hidasi, Sina Honari, Arjun Jain, Sébastien Jean, Kai Jia, Mikhail Korobov, Vivek Kulkarni, Alex Lamb, Pascal Lamblin, Eric Larsen, César Laurent, Sean Lee, Simon Lefrançois, Simon Lemieux, Nicholas Léonard, Zhouhan Lin, Jesse A. Livezey, Cory Lorenz, Jeremiah Lowin, Qianli Ma, Pierre-Antoine Manzagol, Olivier Mastropietro, Robert McGibbon, Roland Memisevic, Bart van Merriënboer, Vincent Michalski, Mehdi Mirza, Alberto Orlandi, Christopher Joseph Pal, Razvan Pascanu, Mohammad Pezeshki, Colin Raffel, Daniel Renshaw, Matthew Rocklin, Adriana Romero, Markus Roth, Peter Sadowski, John Salvatier, François Savard, Jan Schlüter, John Schulman, Gabriel Schwartz, Iulian Vlad Serban, Dmitriy Serdyuk, Samira Shabanian, Étienne Simon, Sigurd Spieckermann, S. Ramana Subramanyam, Jakub Sygnowski, Jérémie Tanguay, Gijs van Tulder, Joseph P. Turian, Sebastian Urban, Pascal Vincent, Francesco Visin, Harm de Vries, David Warde-Farley, Dustin J. Webb, Matthew Willson, Kelvin Xu, Lijun Xue, Li Yao, Saizheng Zhang, Ying Zhang

CoRR, 2016

2013

Stacked calibration of off-policy policy evaluation for video game matchmaking.

Eric Thibodeau-Laufer, Raul Chandias Ferrari, Li Yao, Olivier Delalleau, Yoshua Bengio

Proceedings of the 2013 IEEE Conference on Computational Inteligence in Games (CIG), 2013

2012

Beyond Skill Rating: Advanced Matchmaking in Ghost Recon Online.

Olivier Delalleau, Emile Contal, Eric Thibodeau-Laufer, Raul Chandias Ferrari, Yoshua Bengio, Frank Zhang

IEEE Trans. Comput. Intell. AI Games, 2012

Efficient EM Training of Gaussian Mixtures with Missing Data

Olivier Delalleau, Aaron C. Courville, Yoshua Bengio

CoRR, 2012

Detonation Classification from acoustic Signature with the Restricted Boltzmann Machine.

Yoshua Bengio, Nicolas Chapados, Olivier Delalleau, Hugo Larochelle, Xavier Saint-Mleux, Christian Hudon, Jérôme Louradour

Comput. Intell., 2012

2011

Shallow vs. Deep Sum-Product Networks.

Olivier Delalleau, Yoshua Bengio

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

On the Expressive Power of Deep Architectures.

Yoshua Bengio, Olivier Delalleau

Proceedings of the Algorithmic Learning Theory - 22nd International Conference, 2011

2010

Tempered Markov Chain Monte Carlo for training of Restricted Boltzmann Machines.

Guillaume Desjardins, Aaron C. Courville, Yoshua Bengio, Pascal Vincent, Olivier Delalleau

Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Decision trees do not generalize to new variations.

Yoshua Bengio, Olivier Delalleau, Clarence Simard

Comput. Intell., 2010

2009

Justifying and Generalizing Contrastive Divergence.

Yoshua Bengio, Olivier Delalleau

Neural Comput., 2009

2006

Spectral Dimensionality Reduction.

Yoshua Bengio, Olivier Delalleau, Nicolas Le Roux, Jean-François Paiement, Pascal Vincent, Marie Ouimet

Proceedings of the Feature Extraction - Foundations and Applications, 2006

Large-Scale Algorithms.

Olivier Delalleau, Yoshua Bengio, Nicolas Le Roux

Proceedings of the Semi-Supervised Learning, 2006

Label Propagation and Quadratic Criterion.

Yoshua Bengio, Olivier Delalleau, Nicolas Le Roux

Proceedings of the Semi-Supervised Learning, 2006

2005

Convex Neural Networks.

Yoshua Bengio, Nicolas Le Roux, Pascal Vincent, Olivier Delalleau, Patrice Marcotte

Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

The Curse of Highly Variable Functions for Local Kernel Machines.

Yoshua Bengio, Olivier Delalleau, Nicolas Le Roux

Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

Efficient Non-Parametric Function Induction in Semi-Supervised Learning.

Olivier Delalleau, Yoshua Bengio, Nicolas Le Roux

Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, 2005

2004

Learning Eigenfunctions Links Spectral Embedding and Kernel PCA.

Yoshua Bengio, Olivier Delalleau, Nicolas Le Roux, Jean-François Paiement, Pascal Vincent, Marie Ouimet

Neural Comput., 2004

Locally Linear Embedding for dimensionality reduction in QSAR.

Pierre-Jean L'Heureux, Julie Carreau, Yoshua Bengio, Olivier Delalleau, Shi Yi Yue

J. Comput. Aided Mol. Des., 2004

2003

Out-of-Sample Extensions for LLE, Isomap, MDS, Eigenmaps, and Spectral Clustering.

Yoshua Bengio, Jean-François Paiement, Pascal Vincent, Olivier Delalleau, Nicolas Le Roux, Marie Ouimet

Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003