Benjamin Thérien

26 papers A* 1A 1Journal 20Unranked 4
YearRankTypeTitle / Venue / Authors
2026 J jnl
Covenant-72B: Pre-Training a 72B LLM with Trustless Peers Over-the-Internet.
CoRR
Joel Lidin, Amir Sarfi, Erfan Miahi, Quentin Anthony, Shivam Chauhan, Evangelos Pappas, Benjamin Thérien, Eugene Belilovsky, Samuel Dare
2025 J jnl
Beyond Cosine Decay: On the effectiveness of Infinite Learning Rate Schedule for Continual Pre-training.
CoRR
Vaibhav Singh, Paul Janson, Paria Mehrbod, Adam Ibrahim, Irina Rish, Eugene Belilovsky, Benjamin Thérien
2025 J jnl
Communication Efficient LLM Pre-training with SparseLoCo.
CoRR
Amir Sarfi, Benjamin Thérien, Joel Lidin, Eugene Belilovsky
2025 J jnl
Continual Pre-training of MoEs: How robust is your router?
CoRR
Benjamin Thérien, Charles-Étienne Joseph, Zain Sarwar, Ashwinee Panda, Anirban Das, Shi-Xiong Zhang, Stephen Rawls, Sambit Sahu, Eugene Belilovsky, Irina Rish
2025 J jnl
Continual Pre-training of MoEs: How robust is your router?
Trans. Mach. Learn. Res.
Benjamin Thérien, Charles-Étienne Joseph, Zain Sarwar, Ashwinee Panda, Anirban Das, Shi-Xiong Zhang, Stephen Rawls, Sambit Sahu, Eugene Belilovsky, Irina Rish
2025 J jnl
Dense Backpropagation Improves Training for Sparse Mixture-of-Experts.
CoRR
Ashwinee Panda, Vatsal Baherwani, Zain Sarwar, Benjamin Thérien, Supriyo Chakraborty, Tom Goldstein
2025 J jnl
Meta-learning Optimizers for Communication-Efficient Learning.
Trans. Mach. Learn. Res.
Charles-Étienne Joseph, Benjamin Thérien, Abhinav Moudgil, Boris Knyazev, Eugene Belilovsky
2025 J jnl
MuLoCo: Muon is a practical inner optimizer for DiLoCo.
CoRR
Benjamin Thérien, Xiaolong Huang, Irina Rish, Eugene Belilovsky
2025 J jnl
PyLO: Towards Accessible Learned Optimizers in PyTorch.
CoRR
Paul Janson, Benjamin Thérien, Quentin Anthony, Xiaolong Huang, Abhinav Moudgil, Eugene Belilovsky
2025 J jnl
Revisiting Replay and Gradient Alignment for Continual Pre-Training of Large Language Models.
CoRR
Istabrak Abbes, Gopeshh Subbaraj, Matthew Riemer, Nizar Islah, Benjamin Thérien, Tsuguchika Tabaru, Hiroaki Kingetsu, Sarath Chandar, Irina Rish
2024 — conf
Dense Backpropagation Improves Routing for Sparsely-Gated Mixture-of-Experts.
ENLSP
Ashwinee Panda, Vatsal Baherwani, Zain Sarwar, Benjamin Thérien, Sambit Sahu, Stephen Rawls, Supriyo Chakraborty, Tom Goldstein
2024 A conf
Object Re-Identification from Point Clouds.
WACV
Benjamin Thérien, Chengjie Huang, Adrian Chow, Krzysztof Czarnecki
2024 J jnl
Simple and Scalable Strategies to Continually Pre-train Large Language Models.
CoRR
Adam Ibrahim, Benjamin Thérien, Kshitij Gupta, Mats L. Richter, Quentin Anthony, Timothée Lesort, Eugene Belilovsky, Irina Rish
2024 J jnl
Simple and Scalable Strategies to Continually Pre-train Large Language Models.
Trans. Mach. Learn. Res.
Adam Ibrahim, Benjamin Thérien, Kshitij Gupta, Mats L. Richter, Quentin Gregory Anthony, Eugene Belilovsky, Timothée Lesort, Irina Rish
2024 — conf
StructMoE: Structured Mixture of Experts Using Low Rank Experts.
ENLSP
Zain Sarwar, Ashwinee Panda, Benjamin Thérien, Stephen Rawls, Anirban Das, Kartik Balasubramaniam, Berkcan Kapusuzoglu, Shixiong Zhang, Sambit Sahu, Milind Naphade, Supriyo Chakraborty
2024 J jnl
μLO: Compute-Efficient Meta-Generalization of Learned Optimizers.
CoRR
Benjamin Thérien, Charles-Étienne Joseph, Boris Knyazev, Edouard Oyallon, Irina Rish, Eugene Belilovsky
2023 J jnl
Can We Learn Communication-Efficient Optimizers?
CoRR
Charles-Étienne Joseph, Benjamin Thérien, Abhinav Moudgil, Boris Knyazev, Eugene Belilovsky
2023 J jnl
Continual Pre-Training of Large Language Models: How to (re)warm your model?
CoRR
Kshitij Gupta, Benjamin Thérien, Adam Ibrahim, Mats L. Richter, Quentin Anthony, Eugene Belilovsky, Irina Rish, Timothée Lesort
2023 J jnl
Towards Object Re-Identification from Point Clouds for 3D MOT.
CoRR
Benjamin Thérien, Chengjie Huang, Adrian Chow, Krzysztof Czarnecki
2022 J jnl
A Closer Look at Robustness to L-infinity and Spatial Perturbations and their Composition.
CoRR
Luke Rowe, Benjamin Thérien, Krzysztof Czarnecki, Hongyang Zhang
2022 J jnl
Interpretable Deep Tracking.
CoRR
Benjamin Thérien, Krzysztof Czarnecki
2022 — conf
Out-of-Distribution Detection for LiDAR-based 3D Object Detection.
ITSC
Chengjie Huang, Van Duong Nguyen, Vahdat Abdelzad, Christopher Gus Mannes, Luke Rowe, Benjamin Thérien, Rick Salay, Krzysztof Czarnecki
2022 J jnl
Out-of-Distribution Detection for LiDAR-based 3D Object Detection.
CoRR
Chengjie Huang, Van Duong Nguyen, Vahdat Abdelzad, Christopher Gus Mannes, Luke Rowe, Benjamin Thérien, Rick Salay, Krzysztof Czarnecki
2022 A* conf
Parametric Scattering Networks.
CVPR
Shanel Gauthier, Benjamin Thérien, Laurent Alsène-Racicot, Muawiz Chaudhary, Irina Rish, Eugene Belilovsky, Michael Eickenberg, Guy Wolf
2021 — conf
CLaC-BP at SemEval-2021 Task 8: SciBERT Plus Rules for MeasEval.
SemEval@ACL/IJCNLP
Benjamin Thérien, Parsa Bagherzadeh, Sabine Bergler
2021 J jnl
Parametric Scattering Networks.
CoRR
Shanel Gauthier, Benjamin Thérien, Laurent Alsène-Racicot, Irina Rish, Eugene Belilovsky, Michael Eickenberg, Guy Wolf