Who's Who of AI

Aaron Roth

343 trust researcher @aaroth.bsky.social · 4,315 followers
Professor at Penn, Amazon Scholar at AWS. Interested in machine learning, uncertainty quantification, game theory, privacy, fairness, and most of the intersections therein
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Modern LLMs are incredibly good compression algorithms, which can shed light on why autonomous data science agents don't overfit as much as you might think. arxiv.org/abs/2606.11045

What Fits (Into Few Tokens) Doesn't Overfit: Compression and Generalization in ML Research Agents arxiv.org
AI Weekly's analysis →
  • ML strategies that generalize well can be described in very few tokens, Bertran, Roth, and Wu argue.
  • A reproducer agent given only a brief prompt successfully replicated high-performance models found by a full exploration agent.
  • The framework was tested across 8 datasets covering tabular, vision, language, diffusion, and reward modeling tasks.
Read full analysis →
View on Bluesky · ♥ 23 ↻ 5 ↩ 1 · 2 from the directory shared this · 28d ago
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Recent commentary

AI is getting good at math. What are our jobs as researchers now that we have proof machines? The raw proofs that come from LLMs are difficult to understand, even if correct. So its now easy to quickly write many badly written papers that nevertheless contain correct proofs of interesting theorems.

View on Bluesky · ♥ 7 ↻ 2 ↩ 1 · 7d ago
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