Chmiel, Brian

10 publications

NeurIPS 2025 FP4 All the Way: Fully Quantized Training of Large Language Models Brian Chmiel, Maxim Fishman, Ron Banner, Daniel Soudry

ICLR 2025 Scaling FP8 Training to Trillion-Token LLMs Maxim Fishman, Brian Chmiel, Ron Banner, Daniel Soudry

NeurIPSW 2024 EXAQ: Exponent Aware Quantization for LLMs Acceleration Moran Shkolnik, Maxim Fishman, Brian Chmiel, Hilla Ben-Yaacov, Ron Banner, Kfir Yehuda Levy

ICLR 2023 Accurate Neural Training with 4-Bit Matrix Multiplications at Standard Formats Brian Chmiel, Ron Banner, Elad Hoffer, Hilla Ben-Yaacov, Daniel Soudry

ICLR 2023 Minimum Variance Unbiased N:M Sparsity for the Neural Gradients Brian Chmiel, Itay Hubara, Ron Banner, Daniel Soudry

NeurIPS 2021 Accelerated Sparse Neural Training: A Provable and Efficient Method to Find N:M Transposable Masks Itay Hubara, Brian Chmiel, Moshe Island, Ron Banner, Joseph Naor, Daniel Soudry

JMLR 2021 CAT: Compression-Aware Training for Bandwidth Reduction Chaim Baskin, Brian Chmiel, Evgenii Zheltonozhskii, Ron Banner, Alex M. Bronstein, Avi Mendelson

MLJ 2021 Loss Aware Post-Training Quantization Yury Nahshan, Brian Chmiel, Chaim Baskin, Evgenii Zheltonozhskii, Ron Banner, Alex M. Bronstein, Avi Mendelson

ICLR 2021 Neural Gradients Are Near-Lognormal: Improved Quantized and Sparse Training Brian Chmiel, Liad Ben-Uri, Moran Shkolnik, Elad Hoffer, Ron Banner, Daniel Soudry

NeurIPS 2020 Robust Quantization: One Model to Rule Them All Moran Shkolnik, Brian Chmiel, Ron Banner, Gil Shomron, Yury Nahshan, Alex Bronstein, Uri Weiser