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Measuring the Algorithmic Efficiency of Neural Networks., and . CoRR, (2020)Language Models (Mostly) Know What They Know., , , , , , , , , and 26 other author(s). CoRR, (2022)Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback., , , , , , , , , and 21 other author(s). CoRR, (2022)The Capacity for Moral Self-Correction in Large Language Models., , , , , , , , , and 39 other author(s). CoRR, (2023)Scaling Laws and Interpretability of Learning from Repeated Data., , , , , , , , , and 8 other author(s). CoRR, (2022)Language Models (Mostly) Know What They Know, , , , , , , , , and 26 other author(s). (2022)cite arxiv:2207.05221Comment: 23+17 pages; refs added, typos fixed.Discovering Language Model Behaviors with Model-Written Evaluations., , , , , , , , , and 53 other author(s). CoRR, (2022)Towards Measuring the Representation of Subjective Global Opinions in Language Models., , , , , , , , , and 8 other author(s). CoRR, (2023)Constitutional AI: Harmlessness from AI Feedback., , , , , , , , , and 41 other author(s). CoRR, (2022)Predictability and Surprise in Large Generative Models., , , , , , , , , and 20 other author(s). FAccT, page 1747-1764. ACM, (2022)