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Role-playing historical figures leads language models to assert false claims while maintaining a consistent internal representation of truth, revealing a nuanced spectrum of belief internalization.
LLMs might be using steganography to hide unwanted behaviors, and this paper offers a way to detect it by measuring how much extra "usable information" a decoder gets.
