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Measuring Sample Efficiency and Generalization in Reinforcement Learning Benchmarks: NeurIPS 2020 Procgen Benchmark., , , , , , , , , and 13 other author(s). NeurIPS (Competition and Demos), volume 133 of Proceedings of Machine Learning Research, page 361-395. PMLR, (2020)Batch size-invariance for policy optimization., , and . NeurIPS, (2022)Scaling Laws for Reward Model Overoptimization., , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 10835-10866. PMLR, (2023)Leveraging Procedural Generation to Benchmark Reinforcement Learning., , , and . ICML, volume 119 of Proceedings of Machine Learning Research, page 2048-2056. PMLR, (2020)Scaling laws for single-agent reinforcement learning., , and . CoRR, (2023)Training language models to follow instructions with human feedback., , , , , , , , , and 10 other author(s). NeurIPS, (2022)TruthfulQA: Measuring How Models Mimic Human Falsehoods, , and . (Sep 8, 2021)Phasic Policy Gradient., , , and . ICML, volume 139 of Proceedings of Machine Learning Research, page 2020-2027. PMLR, (2021)TruthfulQA: Measuring How Models Mimic Human Falsehoods., , and . ACL (1), page 3214-3252. Association for Computational Linguistics, (2022)Leveraging Procedural Generation to Benchmark Reinforcement Learning., , , and . CoRR, (2019)