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Leonardo Lavalle

2 accepted papers

2025

Do Large Language Models Understand Word Senses?

EMNLP 2025

Understanding the meaning of words in context is a fundamental capability for Large Language Models (LLMs). Despite extensive evaluation efforts, the extent to which LLMs show evidence that they truly grasp word senses remains underexplored. In this paper, we address this gap by evaluating both i) t

2024

Analyzing Homonymy Disambiguation Capabilities of Pretrained Language Models

COLING 2024main

Word Sense Disambiguation (WSD) is a key task in Natural Language Processing (NLP), aiming to assign the correct meaning (sense) to a word in context. However, traditional WSD systems rely on WordNet as the underlying sense inventory, often differentiating meticulously between subtle nuances of word…