Scaling Laws for Neural Language Models
How model size, training data and compute relate to language-model performance. A foundation for understanding scaling as an empirical relationship, with limits.
Paper & contextMeasuring how loss changes with model size, data, and compute.
Kaplan’s AI research examines how model behavior changes with resources and training choices. These papers connect empirical scaling laws with language-model evaluation, alignment, and defenses against unwanted behavior.
10 papers
How model size, training data and compute relate to language-model performance. A foundation for understanding scaling as an empirical relationship, with limits.
Paper & contextGPT-3 investigates how a large language model can perform tasks from instructions and examples in its prompt, without task-specific weight updates.
Paper & contextConstitutional AI explores training a more helpful and harmless assistant with written principles and AI-generated feedback.
Paper & contextSelected research in ai safety, scaling laws. Read the full paper, including the methods, experiments, and reported results.
Paper & contextBIG-bench collects a broad set of language-model evaluation tasks to study capabilities and limitations beyond a single benchmark.
Paper & contextSelected research in scaling laws. Read the full paper, including the methods, experiments, and reported results.
Paper & contextSelected research in scaling laws, reinforcement learning. Read the full paper, including the methods, experiments, and reported results.
Paper & contextSelected research in scaling laws. Read the full paper, including the methods, experiments, and reported results.
Paper & contextSelected research in ai safety, scaling laws. Read the full paper, including the methods, experiments, and reported results.
Paper & contextSelected research in scaling laws, ai safety. Read the full paper, including the methods, experiments, and reported results.
Paper & contextAn independent editorial profile. Inclusion does not imply Council membership or endorsement. Research is collaborative; coauthorship does not imply sole credit.
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