Kuznedelev, Denis

17 publications

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

ICLR 2026 Scale-Wise Distillation of Diffusion Models Nikita Starodubcev, Ilya Drobyshevskiy, Denis Kuznedelev, Artem Babenko, Dmitry Baranchuk

ICML 2025 Cache Me if You Must: Adaptive Key-Value Quantization for Large Language Models Alina Shutova, Vladimir Malinovskii, Vage Egiazarian, Denis Kuznedelev, Denis Mazur, Surkov Nikita, Ivan Ermakov, Dan Alistarh

ICML 2025 EvoPress: Accurate Dynamic Model Compression via Evolutionary Search Oliver Sieberling, Denis Kuznedelev, Eldar Kurtic, Dan Alistarh

ICLRW 2025 EvoPress: Accurate Dynamic Model Compression via Evolutionary Search Oliver Sieberling, Denis Kuznedelev, Dan Alistarh

NeurIPS 2025 Hogwild! Inference: Parallel LLM Generation via Concurrent Attention Gleb Rodionov, Roman Garipov, Alina Shutova, George Yakushev, Erik Schultheis, Vage Egiazarian, Anton Sinitsin, Denis Kuznedelev, Dan Alistarh

TMLR 2025 TACO Vision Models Can Be Efficiently Specialized via Few-Shot Task-Aware Compression Denis Kuznedelev, Soroush Tabesh, Kimia Noorbakhsh, Elias Frantar, Sara Beery, Eldar Kurtic, Dan Alistarh

TMLR 2024 Accurate Neural Network Pruning Requires Rethinking Sparse Optimization Denis Kuznedelev, Eldar Kurtic, Eugenia Iofinova, Elias Frantar, Alexandra Peste, Dan Alistarh

ICML 2024 Extreme Compression of Large Language Models via Additive Quantization Vage Egiazarian, Andrei Panferov, Denis Kuznedelev, Elias Frantar, Artem Babenko, Dan Alistarh

NeurIPS 2024 PV-Tuning: Beyond Straight-Through Estimation for Extreme LLM Compression Vladimir Malinovskii, Denis Mazur, Ivan Ilin, Denis Kuznedelev, Konstantin Burlachenko, Kai Yi, Dan Alistarh, Peter Richtarik

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

NeurIPS 2024 The Iterative Optimal Brain Surgeon: Faster Sparse Recovery by Leveraging Second-Order Information Diyuan Wu, Ionut-Vlad Modoranu, Mher Safaryan, Denis Kuznedelev, Dan Alistarh

ICLR 2023 A Critical Look at the Evaluation of GNNs Under Heterophily: Are We Really Making Progress? Oleg Platonov, Denis Kuznedelev, Michael Diskin, Artem Babenko, Liudmila Prokhorenkova

ICLR 2023 A View of Mini-Batch SGD via Generating Functions: Conditions of Convergence, Phase Transitions, Benefit from Negative Momenta. Maksim Velikanov, Denis Kuznedelev, Dmitry Yarotsky

NeurIPS 2023 CAP: Correlation-Aware Pruning for Highly-Accurate Sparse Vision Models Denis Kuznedelev, Eldar Kurtić, Elias Frantar, Dan Alistarh

NeurIPS 2023 Characterizing Graph Datasets for Node Classification: Homophily-Heterophily Dichotomy and Beyond Oleg Platonov, Denis Kuznedelev, Artem Babenko, Liudmila Prokhorenkova

NeurIPS 2023 Evaluating Robustness and Uncertainty of Graph Models Under Structural Distributional Shifts Gleb Bazhenov, Denis Kuznedelev, Andrey Malinin, Artem Babenko, Liudmila Prokhorenkova