@inproceedings{tsvigun-etal-2022-altoolbox,
title = "{ALT}oolbox: A Set of Tools for Active Learning Annotation of Natural Language Texts",
author = "Tsvigun, Akim and
Sanochkin, Leonid and
Larionov, Daniil and
Kuzmin, Gleb and
Vazhentsev, Artem and
Lazichny, Ivan and
Khromov, Nikita and
Kireev, Danil and
Rubashevskii, Aleksandr and
Shahmatova, Olga and
Dylov, Dmitry V. and
Galitskiy, Igor and
Shelmanov, Artem",
editor = "Che, Wanxiang and
Shutova, Ekaterina",
booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations",
month = dec,
year = "2022",
address = "Abu Dhabi, UAE",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.emnlp-demos.41",
doi = "10.18653/v1/2022.emnlp-demos.41",
pages = "406--434",
abstract = "We present ALToolbox {--} an open-source framework for active learning (AL) annotation in natural language processing. Currently, the framework supports text classification, sequence tagging, and seq2seq tasks. Besides state-of-the-art query strategies, ALToolbox provides a set of tools that help to reduce computational overhead and duration of AL iterations and increase annotated data reusability. The framework aims to support data scientists and researchers by providing an easy-to-deploy GUI annotation tool directly in the Jupyter IDE and an extensible benchmark for novel AL methods. We prepare a small demonstration of ALToolbox capabilities available online. The code of the framework is published under the MIT license.",
}
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<abstract>We present ALToolbox – an open-source framework for active learning (AL) annotation in natural language processing. Currently, the framework supports text classification, sequence tagging, and seq2seq tasks. Besides state-of-the-art query strategies, ALToolbox provides a set of tools that help to reduce computational overhead and duration of AL iterations and increase annotated data reusability. The framework aims to support data scientists and researchers by providing an easy-to-deploy GUI annotation tool directly in the Jupyter IDE and an extensible benchmark for novel AL methods. We prepare a small demonstration of ALToolbox capabilities available online. The code of the framework is published under the MIT license.</abstract>
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%0 Conference Proceedings
%T ALToolbox: A Set of Tools for Active Learning Annotation of Natural Language Texts
%A Tsvigun, Akim
%A Sanochkin, Leonid
%A Larionov, Daniil
%A Kuzmin, Gleb
%A Vazhentsev, Artem
%A Lazichny, Ivan
%A Khromov, Nikita
%A Kireev, Danil
%A Rubashevskii, Aleksandr
%A Shahmatova, Olga
%A Dylov, Dmitry V.
%A Galitskiy, Igor
%A Shelmanov, Artem
%Y Che, Wanxiang
%Y Shutova, Ekaterina
%S Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
%D 2022
%8 December
%I Association for Computational Linguistics
%C Abu Dhabi, UAE
%F tsvigun-etal-2022-altoolbox
%X We present ALToolbox – an open-source framework for active learning (AL) annotation in natural language processing. Currently, the framework supports text classification, sequence tagging, and seq2seq tasks. Besides state-of-the-art query strategies, ALToolbox provides a set of tools that help to reduce computational overhead and duration of AL iterations and increase annotated data reusability. The framework aims to support data scientists and researchers by providing an easy-to-deploy GUI annotation tool directly in the Jupyter IDE and an extensible benchmark for novel AL methods. We prepare a small demonstration of ALToolbox capabilities available online. The code of the framework is published under the MIT license.
%R 10.18653/v1/2022.emnlp-demos.41
%U https://aclanthology.org/2022.emnlp-demos.41
%U https://doi.org/10.18653/v1/2022.emnlp-demos.41
%P 406-434
Markdown (Informal)
[ALToolbox: A Set of Tools for Active Learning Annotation of Natural Language Texts](https://aclanthology.org/2022.emnlp-demos.41) (Tsvigun et al., EMNLP 2022)
ACL
- Akim Tsvigun, Leonid Sanochkin, Daniil Larionov, Gleb Kuzmin, Artem Vazhentsev, Ivan Lazichny, Nikita Khromov, Danil Kireev, Aleksandr Rubashevskii, Olga Shahmatova, Dmitry V. Dylov, Igor Galitskiy, and Artem Shelmanov. 2022. ALToolbox: A Set of Tools for Active Learning Annotation of Natural Language Texts. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, pages 406–434, Abu Dhabi, UAE. Association for Computational Linguistics.