3 citations · 9 across the 13 of their papers we have counts for
5 papers · 1 filter
Multilingual and Explainable Text Detoxification with Parallel Corpora
Daryna Dementieva, Nikolay Babakov, Amit Ronen +11
Even with various regulations in place across countries and social media platforms (Government of India, 2021; European Parliament and Council of the European Union, 2022, digital…
Explaining Bayesian Networks in Natural Language using Factor Arguments. Evaluation in the medical domain
Jaime Sevilla, Nikolay Babakov, Ehud Reiter +1
In this paper, we propose a model for building natural language explanations for Bayesian Network Reasoning in terms of factor arguments, which are argumentation graphs of flowing…
Scalability of Bayesian Network Structure Elicitation with Large Language Models: a Novel Methodology and Comparative Analysis
Nikolay Babakov, Ehud Reiter, Alberto Bugarin
In this work, we propose a novel method for Bayesian Networks (BNs) structure elicitation that is based on the initialization of several LLMs with different experiences, independen…
Toxicity Classification in Ukrainian
Daryna Dementieva, Valeriia Khylenko, Nikolay Babakov +1
The task of toxicity detection is still a relevant task, especially in the context of safe and fair LMs development. Nevertheless, labeled binary toxicity classification corpora ar…
MultiParaDetox: Extending Text Detoxification with Parallel Data to New Languages
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. Recently, text…