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)

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 Fine-tuning for Inference Acceleration of Large Language Models. - Eldar Kurtic; Denis Kuznedelev; Elias Frantar; Michael Goin; Dan Alistarh (CoRR, 2023)

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

Accurate Compression of Text-to-Image Diffusion Models via Vector Quantization. - Vage Egiazarian; Denis Kuznedelev; Anton Voronov; Ruslan Svirschevski; Michael Goin; Daniil Pavlov; Dan Alistarh; Dmitry Baranchuk (CoRR, 2024)