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Benjamin Thérien
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2020 – today
- 2025
[j3]Charles-Étienne Joseph, Benjamin Thérien, Abhinav Moudgil, Boris Knyazev, Eugene Belilovsky:
Meta-learning Optimizers for Communication-Efficient Learning. Trans. Mach. Learn. Res. 2025 (2025)
[j2]Benjamin Thérien, Charles-Étienne Joseph, Zain Sarwar, Ashwinee Panda, Anirban Das, Shi-Xiong Zhang, Stephen Rawls, Sambit Sahu, Eugene Belilovsky, Irina Rish:
Continual Pre-training of MoEs: How robust is your router? Trans. Mach. Learn. Res. 2025 (2025)
[i16]Vaibhav Singh, Paul Janson, Paria Mehrbod, Adam Ibrahim, Irina Rish, Eugene Belilovsky, Benjamin Thérien:
Beyond Cosine Decay: On the effectiveness of Infinite Learning Rate Schedule for Continual Pre-training. CoRR abs/2503.02844 (2025)
[i15]Benjamin Thérien, Charles-Étienne Joseph, Zain Sarwar, Ashwinee Panda, Anirban Das, Shi-Xiong Zhang, Stephen Rawls, Sambit Sahu, Eugene Belilovsky, Irina Rish:
Continual Pre-training of MoEs: How robust is your router? CoRR abs/2503.05029 (2025)
[i14]Ashwinee Panda, Vatsal Baherwani, Zain Sarwar, Benjamin Thérien, Supriyo Chakraborty, Tom Goldstein:
Dense Backpropagation Improves Training for Sparse Mixture-of-Experts. CoRR abs/2504.12463 (2025)
[i13]Benjamin Thérien, Xiaolong Huang, Irina Rish, Eugene Belilovsky:
MuLoCo: Muon is a practical inner optimizer for DiLoCo. CoRR abs/2505.23725 (2025)
[i12]Paul Janson, Benjamin Thérien, Quentin Anthony, Xiaolong Huang, Abhinav Moudgil, Eugene Belilovsky:
PyLO: Towards Accessible Learned Optimizers in PyTorch. CoRR abs/2506.10315 (2025)
[i11]Istabrak Abbes, Gopeshh Subbaraj, Matthew Riemer, Nizar Islah, Benjamin Thérien, Tsuguchika Tabaru, Hiroaki Kingetsu, Sarath Chandar, Irina Rish:
Revisiting Replay and Gradient Alignment for Continual Pre-Training of Large Language Models. CoRR abs/2508.01908 (2025)
[i10]Amir Sarfi, Benjamin Thérien, Joel Lidin, Eugene Belilovsky:
Communication Efficient LLM Pre-training with SparseLoCo. CoRR abs/2508.15706 (2025)- 2024
[j1]Adam Ibrahim, Benjamin Thérien, Kshitij Gupta, Mats L. Richter, Quentin Gregory Anthony, Eugene Belilovsky, Timothée Lesort, Irina Rish:
Simple and Scalable Strategies to Continually Pre-train Large Language Models. Trans. Mach. Learn. Res. 2024 (2024)
[c6]Ashwinee Panda, Vatsal Baherwani, Zain Sarwar, Benjamin Thérien, Sambit Sahu, Stephen Rawls, Supriyo Chakraborty, Tom Goldstein:
Dense Backpropagation Improves Routing for Sparsely-Gated Mixture-of-Experts. ENLSP 2024: 81-101
[c5]Zain Sarwar, Ashwinee Panda, Benjamin Thérien, Stephen Rawls, Anirban Das, Kartik Balasubramaniam, Berkcan Kapusuzoglu, Shixiong Zhang, Sambit Sahu, Milind Naphade, Supriyo Chakraborty:
StructMoE: Structured Mixture of Experts Using Low Rank Experts. ENLSP 2024: 182-193
[c4]Benjamin Thérien, Chengjie Huang, Adrian Chow, Krzysztof Czarnecki:
Object Re-Identification from Point Clouds. WACV 2024: 8362-8373
[i9]Adam Ibrahim, Benjamin Thérien, Kshitij Gupta, Mats L. Richter, Quentin Anthony, Timothée Lesort, Eugene Belilovsky, Irina Rish:
Simple and Scalable Strategies to Continually Pre-train Large Language Models. CoRR abs/2403.08763 (2024)
[i8]Benjamin Thérien, Charles-Étienne Joseph, Boris Knyazev, Edouard Oyallon, Irina Rish, Eugene Belilovsky:
μLO: Compute-Efficient Meta-Generalization of Learned Optimizers. CoRR abs/2406.00153 (2024)- 2023
[i7]Benjamin Thérien, Chengjie Huang, Adrian Chow, Krzysztof Czarnecki:
Towards Object Re-Identification from Point Clouds for 3D MOT. CoRR abs/2305.10210 (2023)
[i6]Kshitij Gupta, Benjamin Thérien, Adam Ibrahim, Mats L. Richter, Quentin Anthony, Eugene Belilovsky, Irina Rish, Timothée Lesort:
Continual Pre-Training of Large Language Models: How to (re)warm your model? CoRR abs/2308.04014 (2023)
[i5]Charles-Étienne Joseph, Benjamin Thérien, Abhinav Moudgil, Boris Knyazev, Eugene Belilovsky:
Can We Learn Communication-Efficient Optimizers? CoRR abs/2312.02204 (2023)- 2022
[c3]Shanel Gauthier, Benjamin Thérien, Laurent Alsène-Racicot, Muawiz Chaudhary, Irina Rish, Eugene Belilovsky, Michael Eickenberg, Guy Wolf:
Parametric Scattering Networks. CVPR 2022: 5739-5748
[c2]Chengjie Huang, Van Duong Nguyen, Vahdat Abdelzad, Christopher Gus Mannes, Luke Rowe, Benjamin Thérien, Rick Salay, Krzysztof Czarnecki:
Out-of-Distribution Detection for LiDAR-based 3D Object Detection. ITSC 2022: 4265-4271
[i4]Chengjie Huang, Van Duong Nguyen, Vahdat Abdelzad, Christopher Gus Mannes, Luke Rowe, Benjamin Thérien, Rick Salay, Krzysztof Czarnecki:
Out-of-Distribution Detection for LiDAR-based 3D Object Detection. CoRR abs/2209.14435 (2022)
[i3]Benjamin Thérien, Krzysztof Czarnecki:
Interpretable Deep Tracking. CoRR abs/2210.01266 (2022)
[i2]Luke Rowe, Benjamin Thérien, Krzysztof Czarnecki, Hongyang Zhang:
A Closer Look at Robustness to L-infinity and Spatial Perturbations and their Composition. CoRR abs/2210.02577 (2022)- 2021
[c1]Benjamin Thérien, Parsa Bagherzadeh, Sabine Bergler:
CLaC-BP at SemEval-2021 Task 8: SciBERT Plus Rules for MeasEval. SemEval@ACL/IJCNLP 2021: 410-415
[i1]Shanel Gauthier, Benjamin Thérien, Laurent Alsène-Racicot, Irina Rish, Eugene Belilovsky, Michael Eickenberg, Guy Wolf:
Parametric Scattering Networks. CoRR abs/2107.09539 (2021)
Coauthor Index

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last updated on 2025-10-19 21:52 CEST by the dblp team
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