Vage Egiazarian

According to our database, Vage Egiazarian authored at least 24 papers between 2018 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Grid Games: The Power of Multiple Grids for Quantizing Large Language Models.

Vage Egiazarian, Erik Schultheis, Andrei Panferov, Earl Killian, Torsten Hoefler, Dan Alistarh

CoRR, May, 2026

2025

WUSH: Near-Optimal Adaptive Transforms for LLM Quantization.

Jiale Chen, Vage Egiazarian, Torsten Hoefler, Dan Alistarh

CoRR, December, 2025

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

CoRR, September, 2025

AutoJudge: Judge Decoding Without Manual Annotation.

Roman Garipov, Fedor Velikonivtsev, Ruslan Svirschevski, Vage Egiazarian, Max Ryabinin

CoRR, April, 2025

Hogwild! Inference: Parallel LLM Generation via Concurrent Attention.

Gleb Rodionov, Roman Garipov, Alina Shutova, George Yakushev, Vage Egiazarian, Anton Sinitsin, Denis Kuznedelev, Dan Alistarh

CoRR, April, 2025

Unified Scaling Laws for Compressed Representations.

Andrei Panferov, Alexandra Volkova, Ionut-Vlad Modoranu, Vage Egiazarian, Mher Safaryan, Dan Alistarh

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

AutoJudge: Judge Decoding Without Manual Annotation.

Roman Garipov, Fedor Velikonivtsev, Ivan Ermakov, Ruslan Svirschevski, Vage Egiazarian, Max Ryabinin

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Cache Me If You Must: Adaptive Key-Value Quantization for Large Language Models.

Alina Shutova, Vladimir Malinovskii, Vage Egiazarian, Denis Kuznedelev, Denis Mazur, Nikita Surkov, Ivan Ermakov, Dan Alistarh

Proceedings of the Forty-second International Conference on Machine Learning, 2025

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

Rethinking Optimal Transport in Offline Reinforcement Learning.

Arip Asadulaev, Rostislav Korst, Aleksandr Korotin, Vage Egiazarian, Andrey Filchenkov, Evgeny Burnaev

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Extreme Compression of Large Language Models via Additive Quantization.

Vage Egiazarian, Andrei Panferov, Denis Kuznedelev, Elias Frantar, Artem Babenko, Dan Alistarh

Proceedings of the Forty-first International Conference on Machine Learning, 2024

SpQR: A Sparse-Quantized Representation for Near-Lossless LLM Weight Compression.

Tim Dettmers, Ruslan Svirschevski, Vage Egiazarian, Denis Kuznedelev, Elias Frantar, Saleh Ashkboos, Alexander Borzunov, Torsten Hoefler, Dan Alistarh

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Neural Optimal Transport with General Cost Functionals.

Arip Asadulaev, Alexander Korotin, Vage Egiazarian, Petr Mokrov, Evgeny Burnaev

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2022

DEF: deep estimation of sharp geometric features in 3D shapes.

Albert Matveev, Ruslan Rakhimov, Alexey Artemov, Gleb Bobrovskikh, Vage Egiazarian, Emil Bogomolov, Daniele Panozzo, Denis Zorin, Evgeny Burnaev

ACM Trans. Graph., 2022

Neural Optimal Transport with General Cost Functionals.

Arip Asadulaev, Alexander Korotin, Vage Egiazarian, Evgeny Burnaev

CoRR, 2022

Wasserstein Iterative Networks for Barycenter Estimation.

Alexander Korotin, Vage Egiazarian, Lingxiao Li, Evgeny Burnaev

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Wasserstein-2 Generative Networks.

Alexander Korotin, Vage Egiazarian, Arip Asadulaev, Alexander Safin, Evgeny Burnaev

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Latent-space Laplacian Pyramids for Adversarial Representation Learning with 3D Point Clouds.

Vage Egiazarian, Savva Ignatyev, Alexey Artemov, Oleg Voynov, Andrey Kravchenko, Youyi Zheng, Luiz Velho, Evgeny Burnaev

Proceedings of the 15th International Joint Conference on Computer Vision, 2020

Deep Vectorization of Technical Drawings.

Vage Egiazarian, Oleg Voynov, Alexey Artemov, Denis Volkhonskiy, Aleksandr Safin, Maria Taktasheva, Denis Zorin, Evgeny Burnaev

Proceedings of the Computer Vision - ECCV 2020, 2020

2019

Beyond Vector Spaces: Compact Data Representationas Differentiable Weighted Graphs.

Denis Mazur, Vage Egiazarian, Stanislav Morozov, Artem Babenko

CoRR, 2019

Wasserstein-2 Generative Networks.

Alexander Korotin, Vage Egiazarian, Arip Asadulaev, Evgeny Burnaev

CoRR, 2019

Beyond Vector Spaces: Compact Data Representation as Differentiable Weighted Graphs.

Denis Mazur, Vage Egiazarian, Stanislav Morozov, Artem Babenko

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Perceptual Deep Depth Super-Resolution.

Oleg Voynov, Alexey Artemov, Vage Egiazarian, Alexandr Notchenko, Gleb Bobrovskikh, Evgeny Burnaev, Denis Zorin

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

2018

Perceptually-based single-image depth super-resolution.

O. Voinov, Alexey Artemov, Vage Egiazarian, Alexandr Notchenko, Gleb Bobrovskikh, Denis Zorin, Evgeniy Burnaev

CoRR, 2018