Vage Egiazarian

29 papers A* 9Journal 18Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	AutoJudge: Judge Decoding Without Manual Annotation. CoRR Roman Garipov, Fedor Velikonivtsev, Ruslan Svirschevski, Vage Egiazarian, Max Ryabinin
2025	J	`jnl`	Bridging the Gap Between Promise and Performance for Microscaling FP4 Quantization. CoRR Vage Egiazarian, Roberto L. Castro, Denis Kuznedelev, Andrei Panferov, Eldar Kurtic, Shubhra Pandit, Alexandre Noll Marques, Mark Kurtz, Saleh Ashkboos, Torsten Hoefler, Dan Alistarh
2025	A*	`conf`	Cache Me If You Must: Adaptive Key-Value Quantization for Large Language Models. ICML Alina Shutova, Vladimir Malinovskii, Vage Egiazarian, Denis Kuznedelev, Denis Mazur, Nikita Surkov, Ivan Ermakov, Dan Alistarh
2025	J	`jnl`	Cache Me If You Must: Adaptive Key-Value Quantization for Large Language Models. CoRR Alina Shutova, Vladimir Malinovskii, Vage Egiazarian, Denis Kuznedelev, Denis Mazur, Nikita Surkov, Ivan Ermakov, Dan Alistarh
2025	J	`jnl`	Hogwild! Inference: Parallel LLM Generation via Concurrent Attention. CoRR Gleb Rodionov, Roman Garipov, Alina Shutova, George Yakushev, Vage Egiazarian, Anton Sinitsin, Denis Kuznedelev, Dan Alistarh
2025	J	`jnl`	Unified Scaling Laws for Compressed Representations. CoRR Andrei Panferov, Alexandra Volkova, Ionut-Vlad Modoranu, Vage Egiazarian, Mher Safaryan, Dan Alistarh
2025	J	`jnl`	WUSH: Near-Optimal Adaptive Transforms for LLM Quantization. CoRR Jiale Chen, Vage Egiazarian, Torsten Hoefler, Dan Alistarh
2024	J	`jnl`	Accurate Compression of Text-to-Image Diffusion Models via Vector Quantization. CoRR Vage Egiazarian, Denis Kuznedelev, Anton Voronov, Ruslan Svirschevski, Michael Goin, Daniil Pavlov, Dan Alistarh, Dmitry Baranchuk
2024	A*	`conf`	Extreme Compression of Large Language Models via Additive Quantization. ICML Vage Egiazarian, Andrei Panferov, Denis Kuznedelev, Elias Frantar, Artem Babenko, Dan Alistarh
2024	J	`jnl`	Extreme Compression of Large Language Models via Additive Quantization. CoRR Vage Egiazarian, Andrei Panferov, Denis Kuznedelev, Elias Frantar, Artem Babenko, Dan Alistarh
2024	A*	`conf`	Neural Optimal Transport with General Cost Functionals. ICLR Arip Asadulaev, Alexander Korotin, Vage Egiazarian, Petr Mokrov, Evgeny Burnaev
2024	A*	`conf`	Rethinking Optimal Transport in Offline Reinforcement Learning. NeurIPS Arip Asadulaev, Rostislav Korst, Aleksandr Korotin, Vage Egiazarian, Andrey Filchenkov, Evgeny Burnaev
2024	J	`jnl`	Rethinking Optimal Transport in Offline Reinforcement Learning. CoRR Arip Asadulaev, Rostislav Korst, Alexander Korotin, Vage Egiazarian, Andrey Filchenkov, Evgeny Burnaev
2024	A*	`conf`	SpQR: A Sparse-Quantized Representation for Near-Lossless LLM Weight Compression. ICLR Tim Dettmers, Ruslan Svirschevski, Vage Egiazarian, Denis Kuznedelev, Elias Frantar, Saleh Ashkboos, Alexander Borzunov, Torsten Hoefler, Dan Alistarh
2023	J	`jnl`	SpQR: A Sparse-Quantized Representation for Near-Lossless LLM Weight Compression. CoRR Tim Dettmers, Ruslan Svirschevski, Vage Egiazarian, Denis Kuznedelev, Elias Frantar, Saleh Ashkboos, Alexander Borzunov, Torsten Hoefler, Dan Alistarh
2022	J	`jnl`	DEF: deep estimation of sharp geometric features in 3D shapes. ACM Trans. Graph. Albert Matveev, Ruslan Rakhimov, Alexey Artemov, Gleb Bobrovskikh, Vage Egiazarian, Emil Bogomolov, Daniele Panozzo, Denis Zorin, Evgeny Burnaev
2022	J	`jnl`	Neural Optimal Transport with General Cost Functionals. CoRR Arip Asadulaev, Alexander Korotin, Vage Egiazarian, Evgeny Burnaev
2022	A*	`conf`	Wasserstein Iterative Networks for Barycenter Estimation. NeurIPS Alexander Korotin, Vage Egiazarian, Lingxiao Li, Evgeny Burnaev
2022	J	`jnl`	Wasserstein Iterative Networks for Barycenter Estimation. CoRR Alexander Korotin, Vage Egiazarian, Lingxiao Li, Evgeny Burnaev
2021	A*	`conf`	Wasserstein-2 Generative Networks. ICLR Alexander Korotin, Vage Egiazarian, Arip Asadulaev, Alexander Safin, Evgeny Burnaev
2020	—	`conf`	Deep Vectorization of Technical Drawings. ECCV (13) Vage Egiazarian, Oleg Voynov, Alexey Artemov, Denis Volkhonskiy, Aleksandr Safin, Maria Taktasheva, Denis Zorin, Evgeny Burnaev
2020	J	`jnl`	Deep Vectorization of Technical Drawings. CoRR Vage Egiazarian, Oleg Voynov, Alexey Artemov, Denis Volkhonskiy, Aleksandr Safin, Maria Taktasheva, Denis Zorin, Evgeny Burnaev
2020	—	`conf`	Latent-space Laplacian Pyramids for Adversarial Representation Learning with 3D Point Clouds. VISIGRAPP (4: VISAPP) Vage Egiazarian, Savva Ignatyev, Alexey Artemov, Oleg Voynov, Andrey Kravchenko, Youyi Zheng, Luiz Velho, Evgeny Burnaev
2019	A*	`conf`	Beyond Vector Spaces: Compact Data Representation as Differentiable Weighted Graphs. NeurIPS Denis Mazur, Vage Egiazarian, Stanislav Morozov, Artem Babenko
2019	J	`jnl`	Beyond Vector Spaces: Compact Data Representationas Differentiable Weighted Graphs. CoRR Denis Mazur, Vage Egiazarian, Stanislav Morozov, Artem Babenko
2019	J	`jnl`	Latent-Space Laplacian Pyramids for Adversarial Representation Learning with 3D Point Clouds. CoRR Vage Egiazarian, Savva Ignatyev, Alexey Artemov, Oleg Voynov, Andrey Kravchenko, Youyi Zheng, Luiz Velho, Evgeny Burnaev
2019	A*	`conf`	Perceptual Deep Depth Super-Resolution. ICCV Oleg Voynov, Alexey Artemov, Vage Egiazarian, Alexandr Notchenko, Gleb Bobrovskikh, Evgeny Burnaev, Denis Zorin
2019	J	`jnl`	Wasserstein-2 Generative Networks. CoRR Alexander Korotin, Vage Egiazarian, Arip Asadulaev, Evgeny Burnaev
2018	J	`jnl`	Perceptually-based single-image depth super-resolution. CoRR O. Voinov, Alexey Artemov, Vage Egiazarian, Alexandr Notchenko, Gleb Bobrovskikh, Denis Zorin, Evgeniy Burnaev