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Enhancing Mathematical Reasoning with REASONEVAL
Improving LLMs’ Reasoning Process
Mathematical reasoning is crucial for problem-solving and decision-making, especially in large language models (LLMs). However, current evaluation methodologies often focus solely on final accuracy, overlooking logical errors and inefficient steps in the reasoning process.
New Evaluation Approach: REASONEVAL
REASONEVAL is a new approach that goes beyond final-answer accuracy to evaluate the quality of reasoning steps in LLMs. It utilizes validity and redundancy metrics to assess the correctness and efficiency of each reasoning step, providing a more comprehensive evaluation of LLMs’ mathematical reasoning.
Practical Solutions and Value
REASONEVAL’s practical solutions include identifying diverse errors, aiding in data selection for training, and exposing inconsistencies between final-answer accuracy and reasoning step quality. It offers a competitive performance compared to existing methods and can help companies evolve with AI by redefining their work processes and customer engagement.
AI Solutions for Business Transformation
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