Polysemous Word

Polysemous words, those with multiple related meanings, pose a significant challenge to natural language processing and computational linguistics. Current research focuses on how contextual information resolves ambiguity in large language models (LLMs), investigating the role of different model sub-layers and exploring the evolution of polysemy over time using novel approaches like semantic cells and dynamic neural models. These investigations aim to improve the interpretability of LLMs and enhance their ability to accurately process and generate human language, with implications for tasks such as word sense disambiguation and semantic change modeling.