Can Weaker Models Replicate Frontier Discoveries with Hints? Exploring LLM Basins of Attraction
danshipper · x · 2026-08-03
AI researcher Dan Shipper tasked GPT-5.6 with a mathematical challenge before a flight: given a hint involving algebraic number theory, can it reproduce Astra's proof of Erdős's planar unit distance conjecture?
He uses this to propose a broader theory: weaker models can often reproduce frontier-model discoveries if provided with the right conceptual hints. A stronger model's advantage is that it can start farther from the answer, effectively possessing a larger basin of attraction around the correct solution. He suggests this approach could generalize into a novel benchmark for evaluating model generalization and reasoning outside their training data.
Related event: Prompt Distance: Can Weaker Models Reproduce Frontier Proofs?(6 posts)→
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