In neuroscience, we often try to understand systems by analyzing their representations — using tools like regression or RSA. But are these analyses biased towards discovering a subset of what a system represents? If you're interested in this question, check out our new commentary! Thread:

Great new paper by @jessegeerts.bsky.social, looking at a certain type of generalization in transformers -- transitive inference -- and what conditions induce this type of generalization

Jesse Geerts@jessegeerts.bsky.social · last yr.

🧠 How do transformers learn relational reasoning? We trained small transformers on transitive inference (if A>B and B>C, then A>C) and discovered striking differences between learning paradigms. Our latest work reveals when and why AI systems generalize beyond training data 🤖

New paper: Generalization from context often outperforms generalization from finetuning. And you might get the best of both worlds by spending extra compute and train time to augment finetuning.

Andrew Lampinen@lampinen.bsky.social · last yr.

How do language models generalize from information they learn in-context vs. via finetuning? In arxiv.org/abs/2505.00661 we show that in-context learning can generalize more flexibly, illustrating key differences in the inductive biases of these modes of learning — and ways to improve finetuning. 1/

New work led by @aaditya6284.bsky.social "Strategy coopetition explains the emergence and transience of in-context learning in transformers." We find some surprising things!! E.g. that circuits can simultaneously compete AND cooperate ("coopetition") 😯 🧵👇

Sadly, we have lost a brilliant researcher and colleague, Felix Hill. Please see this note, where I have tried to compile some of his writings: docs.google.com/document/d/1...

For Felix

Devastatingly, we have lost a bright light in our field. Felix Hill was not only a deeply insightful thinker -- he was also a generous, thoughtful mentor to many researchers. He majorly changed my lif...

docs.google.com

What counts as in-context learning (ICL)? Typically, you might think of it as learning a task from a few examples. However, we’ve just written a perspective (arxiv.org/abs/2412.03782) suggesting interpreting a much broader spectrum of behaviors as ICL! Quick summary thread: 1/7

The broader spectrum of in-context learning

The ability of language models to learn a task from a few examples in context has generated substantial interest. Here, we provide a perspective that situates this type of supervised few-shot learning...

arxiv.org

Introducing the :milkfoamo: emoji

I'll be not at Neurips this week. Let's grab coffee if you want to fomo-commiserate with me

Hello hello. Testing testing 123