Papers by Domenico Meconi

1 papers
Do Large Language Models Understand Word Senses? (2025.emnlp-main)

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Challenge: Large Language Models (LLMs) have set new performance standards in a wide range of tasks.
Approach: They evaluate the Word Sense Disambiguation capabilities of instruction-tuned LLMs and their ability to understand word senses in three generative settings: definition generation, free-form explanation, and example generation.
Outcome: The proposed models can explain the meaning of words in context with 98% accuracy, while demonstrating greater robustness across domains and levels of difficulty.

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