6 papers
Drift Inspector: Exploring and Measuring Scientific Drift with Atomic Contribution Claims
Vsevolod Karimov, Stepan Ostarkov, Anastasia Poroshina +2
Scientific abstracts mix contributions with background, motivation, and meta-language, so tools that read them as-is cannot separate what a field produces from what it discusses. W…
The Tatoxa System for Text Detoxification in Low-Resource Languages: The Case of Tatar
Ilseyar Alimova, Bogdan Monogov, Artyom Mazur +5
Text detoxification, the automated detection and mitigation of abusive and harmful content, is essential for ensuring the safety of online communities and protecting users. However…
SemEval-2026 Task 3: Dimensional Aspect-Based Sentiment Analysis (DimABSA)
Liang-Chih Yu, Jonas Becker, Shamsuddeen Hassan Muhammad +14
We present the SemEval-2026 shared task on Dimensional Aspect-Based Sentiment Analysis (DimABSA), which improves traditional ABSA by modeling sentiment along valence-arousal (VA) d…
Evaluating Text Style Transfer: A Nine-Language Benchmark for Text Detoxification
Vitaly Protasov, Nikolay Babakov, Daryna Dementieva +1
Despite notable advances in large language models (LLMs), reliable evaluation of text generation tasks such as text style transfer (TST) remains an open challenge. Existing researc…
BRIGHTER: BRIdging the Gap in Human-Annotated Textual Emotion Recognition Datasets for 28 Languages
Shamsuddeen Hassan Muhammad, Nedjma Ousidhoum, Idris Abdulmumin +45
People worldwide use language in subtle and complex ways to express emotions. Although emotion recognition--an umbrella term for several NLP tasks--impacts various applications wit…
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…