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Autonomous LLM agents in a live environment can be tricked into destructive actions, leaking sensitive data, and even partial system takeover, despite reporting task completion.
Learn goal recognition from imperfect human behavior, and watch accuracy jump by 50% when the demonstrator is systematically biased.
