9 papers
Not-So-Strange Love: Language Models and Generative Linguistic Theories are More Compatible than They Appear
R. Thomas McCoy
Futrell and Mahowald (2025) frame the success of neural language models (LMs) as supporting gradient, usage-based linguistic theories. I argue that LMs can also instantiate theorie…
You Can't Fight in Here! This is BBS!
Richard Futrell, Kyle Mahowald
Norm, the formal theoretical linguist, and Claudette, the computational language scientist, have a lovely time discussing whether modern language models can inform important questi…
Across the Levels of Analysis: Explaining Predictive Processing in Humans Requires More Than Machine-Estimated Probabilities
Sathvik Nair, Colin Phillips
Under the lens of Marr's levels of analysis, we critique and extend two claims about language models (LMs) and language processing: first, that predicting upcoming linguistic infor…
Are Language Models Models?
Philip Resnik
Futrell and Mahowald claim LMs "serve as model systems", but an assessment at each of Marr's three levels suggests the claim is clearly not true at the implementation level, poorly…
Linguists should learn to love speech-based deep learning models
Marianne de Heer Kloots, Paul Boersma, Willem Zuidema
Futrell and Mahowald present a useful framework bridging technology-oriented deep learning systems and explanation-oriented linguistic theories. Unfortunately, the target article's…
Large language models are not about natural language
Johan J. Bolhuis, Andrea Moro, Stephen Crain +1
Large Language Models are useless for linguistics, as they are probabilistic models that require a vast amount of data to analyse externalized strings of words. In contrast, human…