no code implementations • HumEval (ACL) 2022 • Varvara Logacheva, Daryna Dementieva, Irina Krotova, Alena Fenogenova, Irina Nikishina, Tatiana Shavrina, Alexander Panchenko
It is often difficult to reliably evaluate models which generate text.
1 code implementation • ACL 2022 • Varvara Logacheva, Daryna Dementieva, Sergey Ustyantsev, Daniil Moskovskiy, David Dale, Irina Krotova, Nikita Semenov, Alexander Panchenko
To the best of our knowledge, these are the first parallel datasets for this task. We describe our pipeline in detail to make it fast to set up for a new language or domain, thus contributing to faster and easier development of new parallel resources. We train several detoxification models on the collected data and compare them with several baselines and state-of-the-art unsupervised approaches.
1 code implementation • ACL 2022 • Daniil Moskovskiy, Daryna Dementieva, Alexander Panchenko
This work investigates multilingual and cross-lingual detoxification and the behavior of large multilingual models in this setting.
1 code implementation • SemEval (NAACL) 2022 • Mikhail Kuimov, Daryna Dementieva, Alexander Panchenko
This paper describes our contribution to SemEval 2022 Task 8: Multilingual News Article Similarity.
no code implementations • 27 Apr 2024 • Daryna Dementieva, Valeriia Khylenko, Nikolay Babakov, Georg Groh
The task of toxicity detection is still a relevant task, especially in the context of safe and fair LMs development.
no code implementations • 2 Apr 2024 • Daryna Dementieva, Nikolay Babakov, Alexander Panchenko
Text detoxification is a textual style transfer (TST) task where a text is paraphrased from a toxic surface form, e. g. featuring rude words, to the neutral register.
no code implementations • 2 Apr 2024 • Daryna Dementieva, Valeriia Khylenko, Georg Groh
Despite the extensive amount of labeled datasets in the NLP text classification field, the persistent imbalance in data availability across various languages remains evident.
no code implementations • 23 Nov 2023 • Daryna Dementieva, Daniil Moskovskiy, David Dale, Alexander Panchenko
Text detoxification is the task of transferring the style of text from toxic to neutral.
no code implementations • 15 May 2023 • Adam Rydelek, Daryna Dementieva, Georg Groh
The Explainable Detection of Online Sexism task presents the problem of explainable sexism detection through fine-grained categorisation of sexist cases with three subtasks.
1 code implementation • 15 May 2023 • Daniel Schroter, Daryna Dementieva, Georg Groh
This paper presents the best-performing approach alias "Adam Smith" for the SemEval-2023 Task 4: "Identification of Human Values behind Arguments".
no code implementations • 6 Mar 2023 • Edoardo Mosca, Daryna Dementieva, Tohid Ebrahim Ajdari, Maximilian Kummeth, Kirill Gringauz, Yutong Zhou, Georg Groh
Interpretability and human oversight are fundamental pillars of deploying complex NLP models into real-world applications.
1 code implementation • 25 Nov 2022 • Daryna Dementieva, Mikhail Kuimov, Alexander Panchenko
In this work, we propose Multiverse -- a new feature based on multilingual evidence that can be used for fake news detection and improve existing approaches.
1 code implementation • 5 Jun 2022 • Daniil Moskovskiy, Daryna Dementieva, Alexander Panchenko
However, models are not able to perform cross-lingual detoxification and direct fine-tuning on exact language is inevitable.
2 code implementations • 19 Apr 2022 • Daryna Dementieva, Nikolay Babakov, Alexander Panchenko
Formality is one of the important characteristics of text documents.
1 code implementation • EMNLP 2021 • David Dale, Anton Voronov, Daryna Dementieva, Varvara Logacheva, Olga Kozlova, Nikita Semenov, Alexander Panchenko
We compare our models with a number of methods for style transfer.
1 code implementation • ACL 2021 • Daryna Dementieva, Alexander Panchenko
Misleading information spreads on the Internet at an incredible speed, which can lead to irreparable consequences in some cases.
3 code implementations • 19 May 2021 • Daryna Dementieva, Daniil Moskovskiy, Varvara Logacheva, David Dale, Olga Kozlova, Nikita Semenov, Alexander Panchenko
We introduce the first study of automatic detoxification of Russian texts to combat offensive language.
no code implementations • SEMEVAL 2020 • Daryna Dementieva, Igor Markov, Alexander Panchenko
This paper presents a solution for the Span Identification (SI) task in the {``}Detection of Propaganda Techniques in News Articles{''} competition at SemEval-2020.