Zobrazeno 1 - 10
of 90 271
pro vyhledávání: '"A. Kuznetsov, A."'
Aiming to help people conduct online research tasks, much research has gone into tools for searching for, collecting, organizing, and synthesizing online information. However, outside of the lab, in-the-wild sensemaking sessions (with data on tasks,
Externí odkaz:
http://arxiv.org/abs/2411.07206
Autor:
Novitskiy, Lev, Lazarev, Vladimir, Tiutiulnikov, Mikhail, Vakhrameev, Nikita, Eremin, Roman, Humonen, Innokentiy, Kuznetsov, Andrey, Dimitrov, Denis, Budennyy, Semen
For a very long time, computational approaches to the design of new materials have relied on an iterative process of finding a candidate material and modeling its properties. AI has played a crucial role in this regard, helping to accelerate the disc
Externí odkaz:
http://arxiv.org/abs/2411.03156
Autor:
Evgeny, Kuznetsov
In this paper, we investigate the concept of local homeomorphism in Esakia spaces. We introduce the notion of etale Heyting H-algebra and establish category-theoretic duality for etale Heyting H-algebra in the case of finite Heyting algebra H. Furthe
Externí odkaz:
http://arxiv.org/abs/2410.23442
Autor:
Arkhipkin, Vladimir, Vasilev, Viacheslav, Filatov, Andrei, Pavlov, Igor, Agafonova, Julia, Gerasimenko, Nikolai, Averchenkova, Anna, Mironova, Evelina, Bukashkin, Anton, Kulikov, Konstantin, Kuznetsov, Andrey, Dimitrov, Denis
Text-to-image (T2I) diffusion models are popular for introducing image manipulation methods, such as editing, image fusion, inpainting, etc. At the same time, image-to-video (I2V) and text-to-video (T2V) models are also built on top of T2I models. We
Externí odkaz:
http://arxiv.org/abs/2410.21061
Autor:
Alekseev, I., Belov, V., Bystryakov, A., Danilov, M., Filosofov, D., Fomina, M., Gorovtsov, P., Iusko, Ye., Kazartsev, S., Khvatov, V., Kiselev, S., Kobyakin, A., Krapiva, A., Kuznetsov, A., Machikhiliyan, I., Mashin, N., Medvedev, D., Nesterov, V., Ponomarev, D., Rozova, I., Rumyantseva, N., Rusinov, V., Samigullin, E., Shevchik, Ye., Shirchenko, M., Shitov, Yu., Skrobova, N., Svirida, D., Tarkovsky, E., Yakushev, E., Zhitnikov, I., Yakovleva, A., Zinatulina, D.
The yields of the inverse beta decay events produced by antineutrinos from a certain nuclear reactor fuel component are used by many experiments to check various model predictions. Yet measurements of the absolute yields feature significant uncertain
Externí odkaz:
http://arxiv.org/abs/2410.19182
Autor:
Alekseev, I., Belov, V., Bystryakov, A., Danilov, M., Filosofov, D., Fomina, M., Gorovtsov, P., Iusko, Ye., Kazartsev, S., Khvatov, V., Kiselev, S., Kobyakin, A., Krapiva, A., Kuznetsov, A., Machikhiliyan, I., Mashin, N., Medvedev, D., Nesterov, V., Ponomarev, D., Rozova, I., Rumyantseva, N., Rusinov, V., Salamatin, A., Samigullin, E., Shevchik, Ye., Shirchenko, M., Shitov, Yu., Skrobova, N., Svirida, D., Tarkovsky, E., Yakushev, E., Zhitnikov, I., Yakovleva, A., Zinatulina, D.
Electron antineutrinos are emitted in the decay chains of the fission products inside a reactor core and could be used for remote monitoring of nuclear reactors. The DANSS detector is placed under the core of the 3.1 GW power reactor at the Kalinin N
Externí odkaz:
http://arxiv.org/abs/2410.18914
Autor:
Kuznetsov, Maksim, Valiev, Airat, Aliper, Alex, Polykovskiy, Daniil, Tutubalina, Elena, Shayakhmetov, Rim, Miftahutdinov, Zulfat
Recent advancements have integrated Language Models (LMs) into a drug discovery pipeline. However, existing models mostly work with SMILES and SELFIES chemical string representations, which lack spatial features vital for drug discovery. Additionally
Externí odkaz:
http://arxiv.org/abs/2410.09240
Blockchain-based sensor networks offer promising solutions for secure and transparent data management in IoT ecosystems. However, efficient set membership proofs remain a critical challenge, particularly in resource-constrained environments. This pap
Externí odkaz:
http://arxiv.org/abs/2410.09169
Machine learning (ML) models trained using Empirical Risk Minimization (ERM) often exhibit systematic errors on specific subpopulations of tabular data, known as error slices. Learning robust representation in presence of error slices is challenging,
Externí odkaz:
http://arxiv.org/abs/2410.08511
Autor:
Kuznetsov, Kristian, Tulchinskii, Eduard, Kushnareva, Laida, Magai, German, Barannikov, Serguei, Nikolenko, Sergey, Piontkovskaya, Irina
Growing amount and quality of AI-generated texts makes detecting such content more difficult. In most real-world scenarios, the domain (style and topic) of generated data and the generator model are not known in advance. In this work, we focus on the
Externí odkaz:
http://arxiv.org/abs/2410.08113