Aggregation of Reasoning: A Hierarchical Framework for Enhancing Answer
Selection in Large Language Models
Aggregation of Reasoning: A Hierarchical Framework for Enhancing Answer
Selection in Large Language Models
Recent advancements in Chain-of-Thought prompting have facilitated significant breakthroughs for Large Language Models (LLMs) in complex reasoning tasks. Current research enhances the reasoning performance of LLMs by sampling multiple reasoning chains and ensembling based on the answer frequency. However, this approach fails in scenarios where the correct answers are in …