Contrastive Chain-of-Thought
Proposes contrastive CoT prompting where models see both valid *and* invalid reasoning demonstrations to reduce reasoning errors.
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Valid + invalid demos: Demonstrations pair correct reasoning traces with common incorrect ones, teaching the model what not to do as well as what to do.
Automatic construction: Provides an automatic method to generate contrastive demonstrations, avoiding the manual curation bottleneck that limited prior CoT variants.
Improves over CoT: Outperforms standard CoT across reasoning benchmarks, with particularly strong gains on problems where common error patterns are predictable.
Pedagogical analog: The improvement mirrors human learning research showing that studying worked examples and errors side-by-side beats studying successes alone.