The Counterfactual
Sean TrottCognitive Science, statistics, AI.
| Platform |  | Pricing | Freemium | Publishes | Weekly |
|---|---|---|---|---|---|
| Issues | 109 | Founded | 4 years ago | Last Issue | 17 days ago |
| Active | |||||
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seantrott.substack.comLatest Issues
How a model got its weights
While writing this piece, an excellent position paper came out on arXiv (Biderman et al., 2026), articulating some of these same arguments about the importance of analyzing training dynamics. I’ve tried to weave some of those arguments into...
Bad habits
In July of 2022—now almost four years ago—I wrote about the possibility that large language models (LLMs) could change the way we use language. This was pre-ChatGPT, but after the release of GPT-3. It was a strange liminal period for resear...
The problem of induction (heads), pt. II
In my last post, I discussed research on induction heads: parts of large language models (LLMs) that learn to attend to repeated sequences in the context and enable LLMs to copy strings of text.
I suggested that as scientific constructs,...
The problem of induction (heads), pt. I
A key aim of mechanistic interpretability research is to identify which internal components of a neural network—like a large language model (LLM)—produce observable behaviors.
Explanations, here, typically reference specific model compone...
Why benchmarks don't resolve disagreements
There are a number of epistemological challenges involved in the study of Large Language Models (LLMs). Foremost among them is evaluation: determining what LLMs can and can’t do is hard, and discussion of their capabilities is thus rife wit...
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The writers behind this newsletter.
Assistant Professor at UC San Diego.
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