The Paradox of Robustness: Decoupling Rule-Based Logic from Affective Noise in High-Stakes Decision-Making

ArXi:2601.21439v2 Announce Type: replace While Large Language Models (LLMs) are widely documented to be sensitive to minor prompt perturbations and prone to sycophantic alignment, their robustness in consequential, rule-bound decision-making remains under-explored. We uncover a striking "Paradox of Robustness": despite their known lexical brittleness, aligned LLMs exhibit strong robustness to emotional framing effects in rule-bound institutional decision-making.