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Large Language Models (LLMs) have achieved significant performance gains through test-time scaling methods.
Cognitive science: History
W. Bechtel, A. Abrahamsen, and G. Graham · 2001
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Chain-of-thought prompting elicits reasoning in large language models
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Llm-blender: Ensembling large language models with pairwise ranking and generative fusion
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Self-refine: Iterative refinement with self-feedback
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Automatic chain of thought prompting in large language models
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Progressive-hint prompting improves reasoning in large language models
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Least-to-most prompting enables complex reasoning in large language models
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Demystifying long chain-of-thought reasoning in llms
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