Redundancy-Aware Self-Consistency for Efficient LLM Reasoning
Large language models increasingly solve multi-step reasoning tasks, where a single sampled chain of reasoning is frequently unreliable. Reaching a correct answer therefore requires aggregating many sampled reasoning paths into one trustworthy decision. The dominant family, self-consistency and its sampling-and-voting...