LeCun Probes LLM Generalization: Do Models Derive x=½at² or Just Interpolate?
ylecun · x · 2026-10-11
Tom Dietterich poses a generalization test: given (x,t) pairs of an object under constant acceleration, can LLMs infer the universal rule x = ½at², or are they just doing kernel interpolation on the pairs?
Yann LeCun replies that insisting models express results with a small number of short formulas using common mathematical primitives is itself an inductive bias / regularizer — the same one symbolic regression employs — and asks why we consider that preference good in the first place.
The exchange touches the core debate over whether LLMs learn actual physical laws or merely interpolate.
Related event: Dietterich and LeCun Debate Whether LLMs Generalize or Just Interpolate(3 posts)→
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