Tom McCoy

Still waiting for Google to release Ge (the large version of Gemini)

Come be my colleague!

The Yale Dept of Linguistics is hiring a 3-year Lecturer in Historical Linguistics. There's a great group here working on language change, and you could become part of it!

Application review begins Dec 14. For more info, see apply.interfolio.com/177395

Image of a Laffy Taffy wrapper. The joke asks "What do you deserve and is also a type of bagel?" And the answer is "Everything"

I am partial to Laffy Taffy mainly because of this one (via www.reddit.com/r/wholesomem...)

I need to know what joke prompted this!!

Ooh jackpot!! Thanks Adina!!

Nice, thank you!

Question motivated by a talk by Squid Tamar-Mattis!

Do any languages have different forms of "and" for different phrase types?

English uses "and" no matter what's being joined: "bread and butter" (nouns), "divide and conquer" (verbs), "short and sweet" (adjs). Are there languages that vary the conjunction across these contexts?

I mean, that's basically what doing a postdoc is!

More info about my research: rtmccoy.com/research/

Top: A syntax tree for the sentence "the doctor by the lawyer saw the artist". Bottom: A continuous vector.

🤖🧠I'll be considering applications for PhD students & postdocs to start at Yale in Fall 2026!

If you are interested in the intersection of linguistics, cognitive science, & AI, I encourage you to apply!

PhD link: rtmccoy.com/prospective_...
Postdoc link: rtmccoy.com/prospective_...

Thanks for the very clear summary of our work, Ben!!

Who's up for a short thread demonstrating just how wrong this claim is by Mistral's CEO, using research by @rtommccoy.bsky.social (an co-authors) regarding crossword puzzles? Just me? Well whatever, let's dive into a mini-exploration of the Embers of Autoregression and why they singe...

I’m excited to share our Findings of EMNLP paper w/ @cocoscilab.bsky.social , @rtommccoy.bsky.social, and @rdhawkins.bsky.social !

Language models, unlike humans, require large amounts of data, which suggests the need for an inductive bias.
But what kind of inductive biases do we need?

An exciting postdoc opportunity for researchers in CogSci!

The deadline is coming up soon: Nov 10

Come be my colleague! The Wu Tsai Institute at Yale has two faculty searches ongoing:
- One in computational cognitive science (due Dec 1)
- One in neurodevelopment (rolling)

🧠🤖

Congratulations - it's very well deserved!!

Much as "cupboard" is pronounced "cubberd", I think that "clipboard" should be pronounced "clibberd"

Beginning a Grand Tour of California!
- Oct 6: Colloquium at Berkeley Linguistics
- Oct 9: Workshop at Google Mountain View
- Oct 14: Talk at UC Irvine Center for Lg, Intelligence & Computation
- Oct 16: NLP / Text-as-Data talk at NYU

Say hi if you'll be around!

Exciting talk in the linguistics department at UC Berkeley tomorrow!
@rtommccoy.bsky.social

Yes!! An excellent point!!

Illustration of the blog post's main argument, summarized as: "Theory of Mind as a Central Skill for Researchers: Research involves many skills.If each skill is viewed separately, each one takes a long time to learn. These skills can instead be connected via theory of mind – the ability to reason about the mental states of others. This allows you to transfer your abilities across areas, making it easier to gain new skills."

🤖 🧠 NEW BLOG POST 🧠 🤖

What skills do you need to be a successful researcher?

The list seems long: collaborating, writing, presenting, reviewing, etc

But I argue that many of these skills can be unified under a single overarching ability: theory of mind

rtmccoy.com/posts/theory...

Totally. I think one key question is whether you want to model the whole developmental process or just the end state. If just the end state, LLMs have a lot to offer; but if the whole development (which is what we ultimately should aim for!) there are many issues in how LLMs get there

The conversation that frequently plays out is:

A: "LLMs do lots of compositional things!"
B: "But they also make lots of mistakes!"
A: "But so do humans!"

I don't find that very productive, so would love to see the field move toward more detailed/contentful comparisons.

They're definitely not fully systematic, so currently it kinda comes down to personal opinion about how systematic is systematic enough. And one thing I would love to see is more systematic head-to-head comparisons of humans and neural networks so that we don't need to rely on intuitions.

Yeah, I think that's a good definition! I also believe that some LLM behaviors qualify as this - they routinely generate sentences with a syntactic structure that never appeared in the training set.

"Hello world!" sounds like a word followed by a crossword clue for that word: "Hell = Low world"

And although models still make lots of mistakes on compositionality, that alone also isn't enough because humans do too. So, if we want to make claims about models being human-like or not, what we really need are finer-grained characterizations of what human-like compositionality is.

Agreed with these points broadly! But though being less “bad at compositionality” isn’t the same as compositional like humans, it does mean that we can no longer say "models completely fail at compositionality and are thus non human like" (because they no longer completely fail).

I agree that garden paths & agreement attraction could be explained with fairly superficial statistics. For priming, what I had in mind was syntactic priming, which I do think requires some sort of structural abstraction.