Dominik Schlechtweg

Insights from Transfer Learning Experiments with Word-in-Context and Word Sense Disambiguation Models

Findings highlight the complementary nature of WiC and WSD and demonstrate that unified training strategies can yield more robust and generalizable sense disambiguation models, and provide practical guidance for designing datasets and models in multilingual and low-resource contexts.