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The Astropy Project: Sustaining and Growing a Community-oriented Open-source Project and the Latest Major Release (v5.0) of the Core Package, , , , , , , , , and 126 other author(s). (2022)cite arxiv:2206.14220Comment: 43 pages, 5 figures. To appear in ApJ. The author list has two parts: the authors that made significant contributions to the writing and/or coordination of the paper, followed by maintainers of and contributors to the Astropy Project. The position in the author list does not correspond to contributions to the Astropy Project as a whole.Toy Models of Superposition., , , , , , , , , and 6 other author(s). CoRR, (2022)Hypothesis: A new approach to property-based testing., and . J. Open Source Softw., 4 (43): 1891 (2019)Predictability and Surprise in Large Generative Models., , , , , , , , , and 20 other author(s). FAccT, page 1747-1764. ACM, (2022)Falsify your Software: validating scientific code with property-based testing.. SciPy, page 162-165. scipy.org, (2020)Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned., , , , , , , , , and 26 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.The Capacity for Moral Self-Correction in Large Language Models., , , , , , , , , and 39 other author(s). CoRR, (2023)Language Models (Mostly) Know What They Know., , , , , , , , , and 26 other author(s). CoRR, (2022)Towards Understanding Sycophancy in Language Models., , , , , , , , , and 9 other author(s). CoRR, (2023)