A Precis of Language Models are not Models of Language
This challenges the foundational assumptions in NLP and AI, indicating an incremental critique rather than a breakthrough.
The paper argues that large neural language models, despite their success in linguistic tasks, are not comprehensive models of natural language, and suggests they do not revolutionize our understanding of cognition.
Natural Language Processing is one of the leading application areas in the current resurgence of Artificial Intelligence, spearheaded by Artificial Neural Networks. We show that despite their many successes at performing linguistic tasks, Large Neural Language Models are ill-suited as comprehensive models of natural language. The wider implication is that, in spite of the often overbearing optimism about AI, modern neural models do not represent a revolution in our understanding of cognition.