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Identity drift in generative agents reveals that anti-self-deception is a dominant modification behavior, challenging assumptions about agent fidelity under pressure.
Simulating 8.3 billion diverse personas reveals nuanced user interactions that traditional evaluations miss, transforming how we assess AI systems.
Quantizing ASR models can actually *improve* performance on rare words, without hurting overall accuracy, by strategically re-weighting the calibration data.
