Inducing and Exploiting Activation Sparsity for Fast Inference on Deep Neural Networks. - Mark Kurtz; Justin Kopinsky; Rati Gelashvili; Alexander Matveev; John Carr; Michael Goin; William M. Leiserson; Sage Moore; Nir Shavit; Dan Alistarh (ICML, 2020)

How Well Do Sparse ImageNet Models Transfer? - Eugenia Iofinova; Alexandra Peste; Mark Kurtz; Dan Alistarh (CVPR, 2022)

The Optimal BERT Surgeon: Scalable and Accurate Second-Order Pruning for Large Language Models. - Eldar Kurtic; Daniel Campos; Tuan Nguyen; Elias Frantar; Mark Kurtz; Benjamin Fineran; Michael Goin; Dan Alistarh (EMNLP, 2022)

Sparse*BERT: Sparse Models are Robust. - Daniel Campos; Alexandre Marques; Tuan Nguyen; Mark Kurtz; ChengXiang Zhai (CoRR, 2022)

oBERTa: Improving Sparse Transfer Learning via improved initialization, distillation, and pruning regimes. - Daniel Campos; Alexandre Marques; Mark Kurtz; ChengXiang Zhai (SustaiNLP, 2023)

Enabling High-Sparsity Foundational Llama Models with Efficient Pretraining and Deployment. - Abhinav Agarwalla; Abhay Gupta; Alexandre Marques; Shubhra Pandit; Michael Goin; Eldar Kurtic; Kevin Leong; Tuan Nguyen; Mahmoud Salem; Dan Alistarh; Sean Lie; Mark Kurtz (CoRR, 2024)