Danil Kireev


2022

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ALToolbox: A Set of Tools for Active Learning Annotation of Natural Language Texts
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 | Artem Shelmanov
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations

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 a href=”http://demo.nlpresearch.group”online/a. A demo video for ALToolbox is provided at: a href=”http://demo-video.nlpresearch.group”http://demo-video.nlpresearch.group/a.The code of the framework is a href=”https://github.com/AIRI-Institute/al_toolbox”published/a under the MIT license.