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Language Models (Mostly) Know What They Know, , , , , , , , , and 26 other author(s). (2022)cite arxiv:2207.05221Comment: 23+17 pages; refs added, typos fixed.The Capacity for Moral Self-Correction in Large Language Models., , , , , , , , , and 39 other author(s). CoRR, (2023)Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models., , , , , , , , , and 440 other author(s). Trans. Mach. Learn. Res., (2023)Language Models (Mostly) Know What They Know., , , , , , , , , and 26 other author(s). CoRR, (2022)In-context Learning and Induction Heads., , , , , , , , , and 16 other author(s). CoRR, (2022)Specific versus General Principles for Constitutional AI., , , , , , , , , and 26 other author(s). CoRR, (2023)Discovering Language Model Behaviors with Model-Written Evaluations., , , , , , , , , and 53 other author(s). ACL (Findings), page 13387-13434. Association for Computational Linguistics, (2023)Motion Analysis and Reconstruction of Human Joint Regions for Sparse RGBD Images., , , and . VR Workshops, page 773-774. IEEE, (2023)Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models., , , , , , , , , and 440 other author(s). CoRR, (2022)Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned., , , , , , , , , and 26 other author(s). CoRR, (2022)