Multiple-Choice Evaluations May Overestimate Models
mervenoyann · x · 2026-07-14
The author argues that when evaluating large models, many MCQA (multiple-choice) evaluations are almost like "cheating" for the models.
The reasoning is that even if a model loops or diverges, the multiple-choice format helps it structure its answer and pull the output "back on track." Therefore, such evaluations may not accurately reflect the model's true capabilities. Ultimately, the author leans towards trusting more holistic, intuitive assessments like the vibe test.
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