SkoltechNLP at SemEval-2022 Task 8: Multilingual News Article Similarity via Exploration of News Texts to Vector Representations

Mikhail Kuimov, Daryna Dementieva, Alexander Panchenko

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper describes our contribution to SemEval 2022 Task 8 on Multilingual News Article Similarity. The aim was to test completely different approaches and distinguish the best performing. That is why we've considered systems based on Transformer-based encoders, NER-based, and NLI-based methods (and their combination with SVO dependency triplets representation). The results prove that Transformer models produce the best scores. However, there is space for research and approaches that give not yet comparable but more interpretable results.

Original languageEnglish
Title of host publicationSemEval 2022 - 16th International Workshop on Semantic Evaluation, Proceedings of the Workshop
EditorsGuy Emerson, Natalie Schluter, Gabriel Stanovsky, Ritesh Kumar, Alexis Palmer, Nathan Schneider, Siddharth Singh, Shyam Ratan
PublisherAssociation for Computational Linguistics (ACL)
Pages1136-1144
Number of pages9
ISBN (Electronic)9781955917803
Publication statusPublished - 2022
Event16th International Workshop on Semantic Evaluation, SemEval 2022 - Seattle, United States
Duration: 14 Jul 202215 Jul 2022

Publication series

NameSemEval 2022 - 16th International Workshop on Semantic Evaluation, Proceedings of the Workshop

Conference

Conference16th International Workshop on Semantic Evaluation, SemEval 2022
Country/TerritoryUnited States
CitySeattle
Period14/07/2215/07/22

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