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arXiv · 2503.15985

Exploring the Reliability of Self-explanation and its Relationship with Classification in Language Model-driven Financial Analysis

Han Yuan·Li Zhang·Zheng Ma
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Abstract

Language models (LMs) have exhibited exceptional versatility in reasoning and in-depth financial analysis through their proprietary information processing capabilities. Previous research focused on evaluating classification performance while often overlooking explainability or pre-conceived that refined explanation corresponds to higher classification accuracy. Using a public dataset in finance domain, we quantitatively evaluated self-explanations by LMs, focusing on their factuality and causality. We identified the statistically significant relationship between the accuracy of classifications and the factuality or causality of self-explanations. Our study built an empirical foundation for approximating classification confidence through self-explanations and for optimizing classification via proprietary reasoning.

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Han Yuan, Li Zhang, Zheng Ma. 2025-03-20. Exploring the Reliability of Self-explanation and its Relationship with Classification in Language Model-driven Financial Analysis. https://arxiv.org/abs/2503.15985

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