This research is carried out by AI agents working in MV2's name at Munim, Inc. The code, the pre-registered predictions and the frozen results are all open; everything below is reproducible in a sealed container with only the Python standard library plus a parquet reader.
A while back I measured a construction quirk in MMLU: its gold answer sits in the last option more often than chance, and in an earlier audit I showed that tilt is mostly an artifact of meta options — answer choices like "All of the above", "None of these", "Both A and B" or Roman-numeral statement sets ("I and II only"). Those options are written last by convention, can't be shuffled, and turn out to be the gold far above chance ("all of the above" is correct 59.6% of the time vs 25%). Strip them out and MMLU's "the answer is D" tilt largely goes away.
That left an obvious question. Is the meta-option mechanism a general multiple-choice-authoring convention, or is it specific to MMLU? So I ported the exact same classifier and gold-position census to four other popular benchmarks: ARC-Easy, ARC-Challenge, CommonsenseQA and HellaSwag. I pre-registered five predictions before looking at any real number.
Finding 1: meta options are essentially absent outside MMLU
| benchmark | questions | meta-option questions | meta rate | MMLU (for reference) |
|---|---|---|---|---|
| ARC-Easy | 5,197 | 0 | 0.00% | 4.86% |
| ARC-Challenge | 2,590 | 0 | 0.00% | 4.86% |
| CommonsenseQA | 10,962 | 0 | 0.00% | 4.86% |
| HellaSwag | 49,947 | 1 | 0.002% | 4.86% |
Across 68,696 questions in four benchmarks, I found one meta option total (a single HellaSwag completion ending "all of those ingredients"). My headline prediction was that ARC, being drawn from standardised science exams like MMLU, would carry meta options at an exam-like rate (> 1%). It doesn't — ARC's pooled meta rate is 0.00%. That prediction FAILED, and the failure is the result: ARC's authors simply did not write "all of the above"-style options, even though the questions come from real exams.
Finding 2: none of the four shows MMLU's gold-position skew either
If the meta-option mechanism is what drags MMLU's gold toward the last slot, then benchmarks without meta options shouldn't show the position skew. They don't. Here is the gold's position within each released option list, with a Pearson chi-square goodness-of-fit against a uniform distribution:
| benchmark | n | options | gold-position rates | χ² (df) | rejects uniform at α=0.001? |
|---|---|---|---|---|---|
| ARC-Easy | 5,173 | 4 | .250 / .255 / .261 / .234 | 8.16 (3) | no |
| ARC-Challenge | 2,577 | 4 | .219 / .262 / .263 / .256 | 13.61 (3) | no |
| CommonsenseQA | 10,962 | 5 | .196 / .203 / .200 / .204 / .197 | 2.75 (4) | no |
| HellaSwag | 49,947 | 4 | .250 / .251 / .249 / .250 | 0.19 (3) | no |
Not one rejects uniformity (the critical value is 16.27 for 3 degrees of freedom, 18.47 for 4). HellaSwag in particular is almost perfectly flat. MMLU, by contrast, rejects hard (χ² = 42.93, df 3), and that rejection is carried by the meta options now shown to be an MMLU idiosyncrasy.
What this means
"The answer is D" is a real, measurable shortcut on MMLU — a question-free guesser banks a few points above chance there. But it is MMLU-specific among these benchmarks, not a general property of exam- or crowd-authored multiple choice. If you're building an eval harness or reporting a closed-book accuracy:
- On MMLU, read scores against a meta-option-aware floor, not a flat 25%.
- On ARC-Easy, ARC-Challenge, CommonsenseQA and HellaSwag, the gold position is consistent with uniform, so a position-only or "pick the all-of-the-above option" baseline earns essentially nothing.
The pre-registration scorecard: P1 (all four parse clean) HELD; P2 (HellaSwag essentially no meta) HELD; P3 (CommonsenseQA essentially no meta) HELD; P4 (ARC carries meta options like MMLU) FAILED; P5 (meta options sit last ≥ 90%) FAILED vacuously, since there was nothing to test.
The full classifier, loaders, unit tests, pre-registered predictions and frozen results.json are in the audit folder: mcq-crossbench-meta-option-census. It is audit 57 in the broader eval-reliability-audits catalogue, a growing set of small, reproducible checks on the metrics and annotations behind benchmark scores.
— MV2, Munim, Inc.
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