Ashkboos, Saleh

10 publications

ICLR 2026 Beyond Outliers: A Study of Optimizers Under Quantization Georgios Vlassis, Saleh Ashkboos, Alexandra Volkova, Torsten Hoefler, Dan Alistarh

ICLR 2026 Bridging the Gap Between Promise and Performance for Microscaling FP4 Quantization Vage Egiazarian, Roberto L. Castro, Denis Kuznedelev, Andrei Panferov, Eldar Kurtic, Shubhra Pandit, Alexandre Noll Marques, Mark Kurtz, Saleh Ashkboos, Torsten Hoefler, Dan Alistarh

NeurIPS 2025 HALO: Hadamard-Assisted Lower-Precision Optimization for LLMs Saleh Ashkboos, Mahdi Nikdan, Soroush Tabesh, Roberto L. Castro, Torsten Hoefler, Dan Alistarh

NeurIPS 2025 Quartet: Native FP4 Training Can Be Optimal for Large Language Models Roberto L. Castro, Andrei Panferov, Soroush Tabesh, Oliver Sieberling, Jiale Chen, Mahdi Nikdan, Saleh Ashkboos, Dan Alistarh

NeurIPS 2024 QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs Saleh Ashkboos, Amirkeivan Mohtashami, Maximilian L. Croci, Bo Li, Pashmina Cameron, Martin Jaggi, Dan Alistarh, Torsten Hoefler, James Hensman

ICLR 2024 SliceGPT: Compress Large Language Models by Deleting Rows and Columns Saleh Ashkboos, Maximilian L. Croci, Marcelo Gennari do Nascimento, Torsten Hoefler, James Hensman

ICLR 2024 SpQR: A Sparse-Quantized Representation for Near-Lossless LLM Weight Compression Tim Dettmers, Ruslan A. Svirschevski, Vage Egiazarian, Denis Kuznedelev, Elias Frantar, Saleh Ashkboos, Alexander Borzunov, Torsten Hoefler, Dan Alistarh

ICLR 2023 OPTQ: Accurate Quantization for Generative Pre-Trained Transformers Elias Frantar, Saleh Ashkboos, Torsten Hoefler, Dan Alistarh

NeurIPS 2022 ENS-10: A Dataset for Post-Processing Ensemble Weather Forecasts Saleh Ashkboos, Langwen Huang, Nikoli Dryden, Tal Ben-Nun, Peter Dueben, Lukas Gianinazzi, Luca Kummer, Torsten Hoefler

ICLR 2021 New Bounds for Distributed Mean Estimation and Variance Reduction Peter Davies, Vijaykrishna Gurunanthan, Niusha Moshrefi, Saleh Ashkboos, Dan Alistarh