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The price of strict fairness in bandit problems can lead to an unavoidable penalty that scales with the number of actions, revealing critical insights for designing fair algorithms.
DPO, a popular RLHF alternative, can actually *hurt* performance due to statistical misspecification, but a simple fix (AuxDPO) can bring it back on track.
