black[LSCDiscovery shared task] GlossReader at LSCDiscovery: Train to Select a Proper Gloss in English – Discover Lexical Semantic Change in Spanish

no code implementations • LChange (ACL) 2022 • Maxim Rachinskiy, Nikolay Arefyev

In order to conclude if there are any differences between senses of a particular word in two corpora, a human annotator or a system shall analyze many examples containing this word from both corpora.

Change Detection XLM-R

GlossReader at SemEval-2021 Task 2: Reading Definitions Improves Contextualized Word Embeddings

no code implementations • SEMEVAL 2021 • Maxim Rachinskiy, Nikolay Arefyev

To verify this hypothesis we developed a solution for the Multilingual and Cross-lingual Word-in-Context (MCL-WiC) task, that does not use any of the shared task data or other WiC data for training.

Task 2 Word Embeddings +3