Large Language Models

I am interested in the differences and similarities in how humans and large language models (LLMs) process pragmatic information. Pragmatic processing involves interpreting language beyond its literal meaning, incorporating context, background knowledge, and social cues. While LLMs have demonstrated exceptional abilities in various language tasks, it remains uncertain whether their capabilities compare to human performance when it comes to more creative tasks, such as the interpretation and generation of novel metaphors, humour comprehension, or other complex aspects of language that may require additional cognitive abilities.In a series of projects, my colleagues and I compare the performance of LLMs (e.g., LLaMA, OLMo, DeepSeek) on various language tasks with human data.

Publications:

Trinley, K., Dzhubaeva, N., & Pissani, L. (2025, submitted). Evaluating LLMs' limitations in narrative experimentation.