Speaker: Ms Sara Court (PhD Student, Department of Linguistics, Ohio State University)
LLMs have solidified their place as a key component of most of today鈥檚 state of the art methods for language technology development.
However, despite their impressive abilities in a number of languages, LLM-based models continue to face challenges that prevent their responsible deployment in real-world applications, particularly in low-resource settings. Sara will present ongoing work she's conducting for her PhD dissertation to develop a potential framework for mitigating the risks and harms associated with LLM-based systems for translation, taking Maltese-English translation as a case study.
The proposed experimental pipeline draws on work using retrieval-augmented generation (RAG) and iterative refinement methods inspired by human translation workflows and morphological theories of the mental lexicon. The ultimate goal is a language-universal framework for a machine translation system that can be easily and safely deployed and improved upon by the very people it is intended to serve.
