Robust Is Salient: An Informed Adversary Moves the Optimal Signal onto the Salience Pole
When an informed adversary shares the audience of a constrained signalling channel, the signal that best protects the truth is the signal that best describes it. On 108 confirmatory items, the adversary-robust optimum aligns exactly with the salience pole from prior work. Across a 200,000-item pool, the two differ on only 2,748 items --- lying exactly where the prior salience-to-Bayes coordinate is undefined. Where defined, robustness is achieved by moving from Bayesian discrimination entirely to salience. We show this by introducing an adversary to a forced-choice task (abstracted from Deception: Murder in Hong Kong). The adversary knows the target, observes the signal, and argues for the strongest wrong answer using a persuasion budget, $β$. As $β$ grows, the optimal signal shifts from the posterior-maximizing option to the margin-maximizing one; at $β= 0$, the game reproduces the original oracle model with a listener temperature of $τ= 1$. This effect is real: 18.2 percent of the pool has an optimum that shifts under a finite budget, and each item's critical budget is exact. This coincidence structurally limits empirical evaluation. Two adversary framings change the chosen…
- arXiv
- 2610.00233
- Authors
- Cris Huynh
- Categories
- cs.AI · cs.CL · cs.GT · cs.LG