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Found 7 papers, 4 papers with code
RuPAWS: A Russian Adversarial Dataset for Paraphrase Identification
We compare it to the largest available dataset for Russian ParaPhraser and show that the best available paraphrase identifiers for the Russian language fail on the RuPAWS dataset.
Detecting Inappropriate Messages on Sensitive Topics that Could Harm a Company’s Reputation
We define a set of sensitive topics that can yield inappropriate and toxic messages and describe the methodology of collecting and labelling a dataset for appropriateness.
Text Detoxification using Large Pre-trained Neural Models
We compare our models with a number of methods for style transfer.
SkoltechNLP at SemEval-2021 Task 5: Leveraging Sentence-level Pre-training for Toxic Span Detection
We show that fine-tuning a RoBERTa model for this problem is a strong baseline.
Methods for Detoxification of Texts for the Russian Language
We introduce the first study of automatic detoxification of Russian texts to combat offensive language.
Detecting Inappropriate Messages on Sensitive Topics that Could Harm a Company's Reputation
We define a set of sensitive topics that can yield inappropriate and toxic messages and describe the methodology of collecting and labeling a dataset for appropriateness.
Active Learning for Sequence Tagging with Deep Pre-trained Models and Bayesian Uncertainty Estimates
Annotating training data for sequence tagging of texts is usually very time-consuming.
