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Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned., , , , , , , , , and 26 other author(s). CoRR, (2022)A General Language Assistant as a Laboratory for Alignment., , , , , , , , , and 12 other author(s). CoRR, (2021)Specific versus General Principles for Constitutional AI., , , , , , , , , and 26 other author(s). CoRR, (2023)In-context Learning and Induction Heads., , , , , , , , , and 16 other author(s). CoRR, (2022)Discovering Language Model Behaviors with Model-Written Evaluations., , , , , , , , , and 53 other author(s). ACL (Findings), page 13387-13434. Association for Computational Linguistics, (2023)Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training., , , , , , , , , and 29 other author(s). CoRR, (2024)Predictability and Surprise in Large Generative Models., , , , , , , , , and 20 other author(s). CoRR, (2022)Constitutional AI: Harmlessness from AI Feedback., , , , , , , , , and 41 other author(s). CoRR, (2022)Discovering Language Model Behaviors with Model-Written Evaluations., , , , , , , , , and 53 other author(s). CoRR, (2022)Predictability and Surprise in Large Generative Models., , , , , , , , , and 20 other author(s). FAccT, page 1747-1764. ACM, (2022)