Pytorch-BigGraph: A Large Scale Graph Embedding System. - Adam Lerer; Ledell Wu; Jiajun Shen; Timothée Lacroix; Luca Wehrstedt; Abhijit Bose; Alex Peysakhovich (SysML, 2019)

PyTorch RPC: Distributed Deep Learning Built on Tensor-Optimized Remote Procedure Calls. - Shen Li; Pritam Damania; Luca Wehrstedt; Rohan Varma; Omkar Salpekar; Pavel Belevich; Howard Huang; Yanli Zhao; Lucas Hosseini; Wanchao Liang; Hongyi Jia; Shihao Xu; et al. (MLSys, 2023)

Hardware Scaling Trends and Diminishing Returns in Large-Scale Distributed Training. - Jared Fernandez; Luca Wehrstedt; Leonid Shamis; Mostafa Elhoushi; Kalyan Saladi; Yonatan Bisk; Emma Strubell; Jacob Kahn (CoRR, 2024)

Efficient Hardware Scaling and Diminishing Returns in Large-Scale Training of Language Models. - Jared Fernandez; Luca Wehrstedt; Leonid Shamis; Mostafa Elhoushi; Kalyan Saladi; Yonatan Bisk; Emma Strubell; Jacob Kahn (Trans. Mach. Learn. Res., 2025)

Accelerating Transformer Inference and Training with 2:4 Activation Sparsity. - Daniel Haziza; Timothy Chou; Dhruv Choudhary; Luca Wehrstedt; Francisco Massa; Jiecao Yu; Geonhwa Jeong; Supriya Rao; Patrick Labatut; Jesse Cai (CoRR, 2025)

DINOv3. - Oriane Siméoni; Huy V. Vo; Maximilian Seitzer; Federico Baldassarre; Maxime Oquab; Cijo Jose; Vasil Khalidov; Marc Szafraniec; Seung Eun Yi; Michaël Ramamonjisoa; Francisco Massa; Daniel Haziza; et al. (CoRR, 2025)