LLM Reasoners: New Evaluation, Library, and Analysis of Step-by-Step Reasoning with Large Language Models

arXiv:2404.05221v1 Announce Type: new
Abstract: Generating accurate step-by-step reasoning is essential for Large Language Models (LLMs) to address complex problems and enhance robustness and interpretability. Despite the flux of research on developing advanced reasoning approaches, systematically analyzing the diverse LLMs and reasoning strategies in generating reasoning chains remains a significant challenge. The difficulties stem from the lack of two key elements: (1) an automatic method for evaluating the generated reasoning chains on different tasks, and (2) a unified formalism and …

abstract advanced analysis and analysis arxiv cs.ai cs.cl diverse evaluation interpretability language language models large language large language models library llm llms reasoning research robustness step-by-step strategies type