CAP-CoT uses iterative adversarial prompt cycles to improve CoT accuracy, stability, and robustness across six benchmarks and four LLM backbones.
Minimiz- ing hallucinations and communication costs: Adversarial debate and voting mechanisms in llm-based multi-agents
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CAP-CoT: Cycle Adversarial Prompt for Improving Chain of Thoughts in LLM Reasoning
CAP-CoT uses iterative adversarial prompt cycles to improve CoT accuracy, stability, and robustness across six benchmarks and four LLM backbones.