Improving LLM Reasoning With Aggregation Of Reasoning Framework
New framework AoR enhances LLMs' complex reasoning by evaluating entire reasoning chains, not just final answers, outperforming current ensemble methods in various tasks.
This is a Plain English Papers summary of a research paper called Aggregation of Reasoning: A Hierarchical Framework for Enhancing Answer Selection in Large Language Models. If you like these kinds of analysis, you should subscribe to the AImodels.fyi newsletter or follow me on Twitter. Overview Recent advancements in Chain-of-Thought prompting have led to significant breakthroughs for Large Language Models (LLMs) in complex reasoning tasks. Current ensemble methods that sample multiple reasoning chains and select answers based on frequency fail in scenarios where the correct answers...