ATGen: A Framework for Active Text Generation
Tsvigun, Akim Vasilev, Daniil Tsvigun, Ivan Lysenko, Ivan Bektleuov, Talgat Medvedev, Aleksandr Vinogradova, Uliana Severin, Nikita Mozikov, Mikhail Savchenko, Andrey
Tsvigun, Akim
Vasilev, Daniil
Tsvigun, Ivan
Lysenko, Ivan
Bektleuov, Talgat
Medvedev, Aleksandr
Vinogradova, Uliana
Severin, Nikita
Mozikov, Mikhail
Savchenko, Andrey
Supervisor
Department
Natural Language Processing
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Type
Conference proceeding
Date
2025
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Language
English
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Abstract
Active learning (AL) has demonstrated remarkable potential in reducing the annotation effort required for training machine learning models. However, despite the surging popularity of natural language generation (NLG) tasks in recent years, the application of AL to NLG has been limited. In this paper, we introduce Active Text Generation (ATGen) – a comprehensive framework that bridges AL with text generation tasks, enabling the application of state-of-the-art AL strategies to NLG. Our framework simplifies AL-empowered annotation in NLG tasks using both human annotators and automatic annotation agents based on large language models (LLMs). The framework supports LLMs deployed as services, such as ChatGPT and Claude, or operated on-premises. Furthermore, ATGen provides a unified platform for smooth implementation and benchmarking of novel AL strategies tailored to NLG tasks. Finally, we present evaluation results for state-of-the-art AL strategies across diverse settings and multiple text generation tasks. We show that ATGen reduces both the effort of human annotators and costs associated with API calls to LLM-based annotation agents. The code of the framework is available on GitHub1 under the MIT license. The video presentation is available at http://atgen-video.nlpresearch.group.
Citation
A. Tsvigun et al., “ATGen: A Framework for Active Text Generation,” vol. 3, pp. 653–665, Aug. 2025, doi: 10.18653/V1/2025.ACL-DEMO.63
Source
Proceedings of the Annual Meeting of the Association for Computational Linguistics
Conference
63rd Annual Meeting of the Association for Computational Linguistics, ACL 2025
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Subjects
Source
63rd Annual Meeting of the Association for Computational Linguistics, ACL 2025
Publisher
Association for Computational Linguistics