Debate: Is LeCun's case against LLM planning defeated by learned self-correction?
teortaxesTex · x · 2026-09-26
teortaxesTex challenges Yann LeCun's argument that LLMs can't plan: since models can learn "oops, that was the wrong token!" behavior, why can't trajectories be improved via local refinement?
- He argues the assumption that the convex hull of correct trajectories must be memorized is flawed
- Trajectories are composed of composable motifs that can reach arbitrarily good optima via local improvement, much like gradient descent itself
- A substantive AI-community debate on whether LLMs truly learn planning/world models
Related event: Debate Erupts Over LeCun's Claim That LLMs Can't Self-Correct(4 posts)→
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