🤖🧠NEW PAPER🧠🤖 Children & neural networks can learn syntax from linear strings of words. How do they do it? Our hypothesis: Word co-occurrence statistics provide cues to syntax! (I.e., a new type of bootstrapping to consider!) Paper: arxiv.org/abs/2605.20529 1/n
Tom McCoy
Articles & links
🤖🧠 New commentary 🧠🤖 What role should large language models (LLMs) play in linguistics? I reflect on this question in a commentary now on arXiv: arxiv.org/abs/2605.10061 To appear in BBS as a commentary on @futrell.bsky.social and @kmahowald.bsky.social's excellent piece on LL…
Link for "Collocational bootstrapping: A hypothesis about the learning of subject-verb agreement in humans and neural networks": aclanthology.org/2026.conll-m...
I’m excited about this paper because statistical regularities sometimes pose a problem for learning abstract syntax (e.g., aclanthology.org/P19-1334/), but these results give an example of how statistics can *support* the right abstractions! For more, see our paper: arxiv.org/…
Recent commentary
Today at #acl2026nlp: Check out the panel on "Linguistics and NLP in the LLM Era", featuring Allyson Ettinger, @futrell.bsky.social, Zoey Liu, and me! 2:00 - 3:30 in Gaslamp C&D
In San Diego for #acl2026nlp! Excited to talk to people about connections between CogSci, Linguistics, and AI
In Tom McCoy's orbit
Center = Tom McCoy. Left = members they follow (green edges). Right = members who follow them (blue edges). Top = mutual follows (orange edges, slightly larger). Drag any node to reposition; click to open that profile.