Research

Computational complexity of reasoning

Which reasoning problems are hard for language models, and why?

We ask whether the systematic failures of model reasoning follow from the computational complexity of the problems themselves, rather than from scale or training, and what complexity theory predicts about where reasoning should break down.

Verification

When can an answer be checked more cheaply than it can be produced?

We study what can be verified, at what cost, and what a reliable check makes possible for systems that reason.

Large-scale empirical evaluation

Does the theory hold when it is tested on real models?

We design evaluations of language models that isolate one reasoning question at a time, and size them in advance so that the result can confirm or refute what the theory predicts.

Publications