Lune

EMNLP Findings2023

Is ChatGPT a Financial Expert? Evaluating Language Models on Financial Natural Language Processing

Yue Guo, Zian Xu, Yi Yang

摘要

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 decoderonly 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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引用它的顶会 Paper2

  1. Fundamental Capabilities of Large Language Models and their Applications in Domain Scenarios: A SurveyJiawei Li, Yizhe Yang, Yu Bai, Xiaofeng Zhou 等ACL 2024 · 15 次引用
  2. LLM-Powered Multi-Agent Collaboration for Intelligent Industrial On-Call AutomationRuowei Fu, Yang Zhang, Zeyu Che, Xin Wu 等ASE 2025

它引用的 Paper5

  1. Language Models are Few-Shot LearnersTom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah 等NeurIPS 2020 · 64,255 次引用
  2. Training language models to follow instructions with human feedbackLong Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida 等NeurIPS 2022 · 24,707 次引用
  3. Self-Instruct: Aligning Language Models with Self-Generated InstructionsYizhong Wang, Yeganeh Kordi, Swaroop Mishra, Alisa Liu 等ACL 2023 · 540 次引用
  4. When FLUE Meets FLANG: Benchmarks and Large Pretrained Language Model for Financial DomainRaj Sanjay Shah, Kunal Chawla, Dheeraj Eidnani, Agam Shah 等EMNLP 2022 · 63 次引用
  5. Trillion Dollar Words: A New Financial Dataset, Task & Market AnalysisAgam Shah, Suvan Paturi, Sudheer ChavaACL 2023 · 27 次引用

相关 Paper

  1. Financial Language Model Evaluation (FLaME)Glenn Matlin, Mika Okamoto, Huzaifa Pardawala, Yang Yang 等ACL Findings 2025 · 3 次引用
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  3. FinMaster: A Holistic Benchmark for Full-Pipeline Financial Management with Large Language ModelsJunzhe Jiang, Chang Yang, Aixin Cui, Sihan Jin 等ACL Findings 2026
  4. Exploring the Impact of Corpus Diversity on Financial Pretrained Language ModelsJaeyoung Choe, Keonwoong Noh, Nayeon Kim, Seyun Ahn 等EMNLP Findings 2023 · 6 次引用
  5. BizBench: A Quantitative Reasoning Benchmark for Business and FinanceMichael Krumdick, Rik Koncel-Kedziorski, Viet Dac Lai, Varshini Reddy 等ACL 2024 · 10 次引用
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