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Chain-of-Thought significantly enhances a model's reasoning capability, but it also comes with a considerable increase in inference costs due to long chains.
Bandit based monte-carlo planning
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Chain-of-thought prompting elicits reasoning in large language models
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Self-consistency improves chain of thought reasoning in language models
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Compressed chain of thought: Efficient reasoning through dense representations
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To cot or not to cot? chain-of-thought helps mainly on math and symbolic reasoning
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Math-shepherd: Verify and reinforce LLMs step-by-step without human annotations
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