Is ChatGPT a Financial Expert? Evaluating Language Models on Financial Natural Language Processing
October 19, 2023 ยท Declared Dead ยท ๐ Conference on Empirical Methods in Natural Language Processing
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Authors
Yue Guo, Zian Xu, Yi Yang
arXiv ID
2310.12664
Category
cs.CL: Computation & Language
Citations
17
Venue
Conference on Empirical Methods in Natural Language Processing
Last Checked
4 months ago
Abstract
The emergence of Large Language Models (LLMs), such as ChatGPT, has revolutionized general natural language preprocessing (NLP) tasks. However, their expertise in the financial domain lacks a comprehensive evaluation. To assess the ability of LLMs to solve financial NLP tasks, we present FinLMEval, a framework for Financial Language Model Evaluation, comprising nine datasets designed to evaluate the performance of language models. This study compares the performance of encoder-only language models and the decoder-only language models. Our findings reveal that while some decoder-only LLMs demonstrate notable performance across most financial tasks via zero-shot prompting, they generally lag behind the fine-tuned expert models, especially when dealing with proprietary datasets. We hope this study provides foundation evaluations for continuing efforts to build more advanced LLMs in the financial domain.
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