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LINGOLY: A Benchmark of Olympiad-Level Linguistic Reasoning Puzzles in Low-Resource and Extinct Languages., , , , , , , and . CoRR, (2024)SimpleSafetyTests: a Test Suite for Identifying Critical Safety Risks in Large Language Models., , , , , , and . CoRR, (2023)The Empty Signifier Problem: Towards Clearer Paradigms for Operationalising Älignment" in Large Language Models., , , and . CoRR, (2023)Auditing large language models: a three-layered approach., , , and . CoRR, (2023)Is More Data Better? Re-thinking the Importance of Efficiency in Abusive Language Detection with Transformers-Based Active Learning., , and . CoRR, (2022)Bias Out-of-the-Box: An Empirical Analysis of Intersectional Occupational Biases in Popular Generative Language Models., , , , , , , and . NeurIPS, page 2611-2624. (2021)Balancing the Picture: Debiasing Vision-Language Datasets with Synthetic Contrast Sets., , , , , and . CoRR, (2023)Introducing v0.5 of the AI Safety Benchmark from MLCommons., , , , , , , , , and 87 other author(s). CoRR, (2024)The benefits, risks and bounds of personalizing the alignment of large language models to individuals., , , and . Nat. Mac. Intell., 6 (4): 383-392 (2024)The PRISM Alignment Project: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language Models., , , , , , , , , and 2 other author(s). CoRR, (2024)