At this semester’s first MCQLL meeting, Eva Portelance will be presenting The roles of neural networks in language acquisition.
All are welcome to attend.
- Eva Portelance
- The roles of neural networks in language acquisition
How can modern neural networks like large language models be useful to the field of language acquisition, and more broadly cognitive science, if they are not a priori designed to be cognitive models? As developments towards natural language understanding and generation have improved leaps and bounds, with models like GPT-4, the question of how they can inform our understanding of human language acquisition has re-emerged. As such, it is critical to examine how in practice linking hypotheses between models and human learners can be safely established. To address these questions, I present a model taxonomy, including four modeling approaches, each having differing goals, from exploratory hypothesis generation to hypothesis differentiation and testing. I ground each approach in the realist vs. instrumentalist debates in philosophy of science and present in practice examples of two of these approaches from my own work.