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Group alignment can lead to unexpected sycophantic behavior, with some demographic groups experiencing greater alignment gains than others, challenging the notion of a one-size-fits-all approach in model adaptation.
LLMs that nail individual personas can still fail spectacularly at generating diverse populations, instead defaulting to coarse stereotypes.
LLMs leak significantly more private information in multi-turn conversations than single-message evaluations suggest, and free-text pseudonymization offers a more robust privacy-utility trade-off than suppression or generalization.
