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Towards Revealing the Mystery behind Chain of Thought: A Theoretical Perspective

NeurIPS 2023 · Large language models › Reasoning and chain of thought · approach: Chain-of-thought training and analysis · 27 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
add chain of thought to a 3-layer transformer (ablation)3-layer transformer · Arithmetic formula, 6 operatorsaccuracy (%): 17.72 -> 99.97Helped
add a layer without CoT (3 to 5 layers) (ablation)transformer without CoT · Arithmetic formula, 6 operatorsaccuracy (%): 17.72 -> 46.19Helped
train on <=14 operators, test on longer formulas3-layer transformer with CoT · Arithmetic formula length generalizationaccuracy (%): 99.9 -> 45.5 (15 to 18 operators)Mixed

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