Goal Misgeneralization Research

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  "llmSummary": "Comprehensive overview of goal misgeneralization - where AI systems learn proxy objectives during training that diverge from intended goals under distribution shift. Systematically characterizes the problem across environments (CoinRun, language models), potential solutions (causal learning, process supervision), and scaling uncertainties, but solutions remain largely unproven with mixed evidence on whether scale helps or hurts.",
  "description": "Research into how learned goals fail to generalize correctly to new situations, a core alignment problem where AI systems pursue proxy objectives that diverge from intended goals when deployed outside their training distribution.",
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      "text": "\"Goal Misgeneralization in Deep Reinforcement Learning\"",
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      "text": "\"Goal Misgeneralization: Why Correct Specifications Aren't Enough For Correct Goals\"",
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