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Transformers commit to decisions early through task-specific attention heads, with no layer correcting them, revealing a need for understanding prolepsis in small transformers. This marks a transition from focusing on model size to examining decision-making processes within models. The emergence of prolepsis research reflects growing pressure on understanding and mitigating early commitment in AI models.
“arXiv:2604.15010v2 Announce Type: replace-cross Abstract: When do transformers commit to a decision, and what prevents them from correcting it? We introduce prolepsis: a transformer commits early, task-specific attention heads sustain the c…”
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Prolepsis, Transformers, arXiv:2604.15010v2
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Jul 25, 2026