Prolepsis in Transformers

SIGNAL ANALYSIS

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.