GPT confidently botches basic representation theory, exposing training-data bias
MvsCerezo · x · 2026-09-29
MvsCerezo shares a model failure case: GPT erred on GL(d) representation theory in quantum mechanics — essentially linear algebra — by extrapolating results from "standard" (holonomic) rep theory to the "non-standard" (non-holonomic) case. He calls it vivid evidence that training data strongly biases the model. Worse, when asked to justify the wrong math, the model kept pushing confidently until the error was explicitly pointed out — "scary."
Related event: GPT's Top Reasoning Tier Confidently Makes Basic Math Error in Proof(3 posts)→
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