Micah Goldblum

We isolate “reasoning embeddings” from LLMs using a residual method and show they uniquely predict brain activity, revealing distinct neural correlates of reasoning beyond shallow linguistic features.

We fit scaling laws for large language models with varying width-to-depth ratios and parameter counts.

We jointly evaluate VLMs and diffusion models by seeing whether VLMs can evaluate diffusion model failure modes.