FLAME: Financial Large-Language Model Assessment and Metrics Evaluation
Guo, Jiayu, Guo, Yu, Li, Martha, Tan, Songtao
–arXiv.org Artificial Intelligence
LLMs have revolutionized NLP and demonstrated potential across diverse domains. More and more financial LLMs have been introduced for finance-specific tasks, yet comprehensively assessing their value is still challenging. In this paper, we introduce FLAME, a comprehensive financial LLMs evaluation system in Chinese, which includes two core evaluation benchmarks: FLAME-Cer and FLAME-Sce. FLAME-Cer covers 14 types of authoritative financial certifications, including CPA, CFA, and FRM, with a total of approximately 16,000 carefully selected questions. All questions have been manually reviewed to ensure accuracy and representativeness. FLAME-Sce consists of 10 primary core financial business scenarios, 21 secondary financial business scenarios, and a comprehensive evaluation set of nearly 100 tertiary financial application tasks. We evaluate 6 representative LLMs, including GPT-4o, GLM-4, ERNIE-4.0,
arXiv.org Artificial Intelligence
Jan-3-2025
- Genre:
- Research Report (1.00)
- Industry:
- Banking & Finance > Trading (1.00)
- Information Technology > Security & Privacy (1.00)
- Technology: