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An interactive AI can fairly evaluate skills across diverse self-presentation styles, ensuring equitable outcomes even when individuals differ in their tendency towards self-promotion or modesty.
Forget single-objective optimization鈥攖his work cracks omniprediction in multiclass settings, opening the door to algorithms that are robust across diverse loss functions and comparator classes.
