Current natural language processing (NLP) models (e.g. ChatGPT, GPT-4, etc.) have impressive capabilities, but how closely do they actually align with the capabilities of the only system that truly understands complex language–the human brain? In this seminar, we will review work that studies the existing alignment between the representations of language constructed by NLP models and the representations of language in the human brain obtained from brain imaging devices, as humans and models process the same language input. We will discuss the reasons for existing alignment, and some of the established remaining gaps. We will additionally review works that aim to bring NLP models closer to the human brain. Lastly, students will have the opportunity to propose and complete related projects.
- Teacher: Gabriele Merlin
- Teacher: Mariya Toneva