Confidence Improves Self-Consistency in LLMs

Understand

Self-consistency decoding enhances LLMs' performance on reasoning tasks by sampling diverse reasoning paths and selecting the most frequent answer.

• However, it is computationally expensive, as sampling many of these (lengthy) paths is required to increase the chances that the correct answer emerges as the most frequent one.
• To address this, we introduce Confidence-Informed Self-Consistency (CISC).
• CISC performs a weighted majority vote based on confidence scores obtained directly from the model.