Zobrazeno 1 - 10
of 724
pro vyhledávání: '"P. A. Boytsov"'
Autor:
P. A. Boytsov, M. L. Dorofeev
Publikováno v:
Вестник университета, Vol 1, Iss 6, Pp 97-105 (2023)
In modern Russia, the initiative budgeting mechanism has been developing systematically since 2015. The practice has been launched in 51 out of 85 constituent entities of the Russian Federation. This phenomenon is an urgent topic for research, in con
Externí odkaz:
https://doaj.org/article/14055d4720674461bf9488f7692add45
Autor:
Titov, Sergey, Evtikhiev, Mikhail, Shapkin, Anton, Smirnov, Oleg, Boytsov, Sergei, Karaeva, Dariia, Sheptyakov, Maksim, Arkhipov, Mikhail, Bryksin, Timofey, Bogomolov, Egor
In this technical report, we present three novel datasets of Kotlin code: KStack, KStack-clean, and KExercises. We also describe the results of fine-tuning CodeLlama and DeepSeek models on this data. Additionally, we present a version of the HumanEva
Externí odkaz:
http://arxiv.org/abs/2405.19250
We introduce KazQAD -- a Kazakh open-domain question answering (ODQA) dataset -- that can be used in both reading comprehension and full ODQA settings, as well as for information retrieval experiments. KazQAD contains just under 6,000 unique question
Externí odkaz:
http://arxiv.org/abs/2404.04487
Autor:
Song, Yewei, Ezzini, Saad, Tang, Xunzhu, Lothritz, Cedric, Klein, Jacques, Bissyandé, Tegawendé, Boytsov, Andrey, Ble, Ulrick, Goujon, Anne
Text-to-SQL, the task of translating natural language questions into SQL queries, is part of various business processes. Its automation, which is an emerging challenge, will empower software practitioners to seamlessly interact with relational databa
Externí odkaz:
http://arxiv.org/abs/2312.14725
Autor:
Meshcheryakov, Georgy, Abramov, Sergey, Boytsov, Aleksandr, Buyan, Andrey I., Makeev, Vsevolod J., Kulakovskiy, Ivan V.
Modern high-throughput sequencing assays efficiently capture not only gene expression and different levels of gene regulation but also a multitude of genome variants. Focused analysis of alternative alleles of variable sites at homologous chromosomes
Externí odkaz:
http://arxiv.org/abs/2306.08287
Autor:
Joshi, Ameya, Pham, Minh, Cho, Minsu, Boytsov, Leonid, Condessa, Filipe, Kolter, J. Zico, Hegde, Chinmay
Randomized smoothing (RS) has been shown to be a fast, scalable technique for certifying the robustness of deep neural network classifiers. However, methods based on RS require augmenting data with large amounts of noise, which leads to significant d
Externí odkaz:
http://arxiv.org/abs/2205.06154
Large multilingual language models such as mBERT or XLM-R enable zero-shot cross-lingual transfer in various IR and NLP tasks. Cao et al. (2020) proposed a data- and compute-efficient method for cross-lingual adjustment of mBERT that uses a small par
Externí odkaz:
http://arxiv.org/abs/2204.06457
Publikováno v:
SIGIR 2021 (44th International ACM SIGIR Conference on Research and Development in Information Retrieval)
Due to high annotation costs making the best use of existing human-created training data is an important research direction. We, therefore, carry out a systematic evaluation of transferability of BERT-based neural ranking models across five English d
Externí odkaz:
http://arxiv.org/abs/2103.03335
Autor:
Ovsyannikov, V. P., Nefiodov, A. V., Boytsov, A. Yu., Ramzdorf, A. Yu., Stegailov, V. I., Tyutyunnikov, S. I., Levin, A. A.
We discuss recent experiments performed with an upgraded version of the main magnetic focus ion source (MaMFIS) at the Joint Institute for Nuclear Research (JINR) in Dubna. The device operates in the range of electron beam energies extended up to $40
Externí odkaz:
http://arxiv.org/abs/2103.01268
SberQuAD -- a large scale analog of Stanford SQuAD in the Russian language - is a valuable resource that has not been properly presented to the scientific community. We fill this gap by providing a description, a thorough analysis, and baseline exper
Externí odkaz:
http://arxiv.org/abs/1912.09723