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Paper Abstract and Keywords
Presentation 2024-09-02 15:10
Performance Analysis of ChatGPT in Solving the CPA Multiple-Choice Exam (Business Law)
Tatsuki Masuda (Keio Univ./RIKEN AIP), Kei Nakagawa (Nomura Asset Management/Osaka Metropolitan Univ.), Kaito Takano (Nomura Asset Management), Takahiro Hoshino (Keio Univ./RIKEN AIP) NLC2024-6
Abstract (in Japanese) (See Japanese page) 
(in English) The accurate perfomance measurement of the response capabilities of large language models~(LLMs) is a crucial issue, especially in the fields of accounting, auditing, and law.
These specialized areas demand high levels of knowledge and logical reasoning as national qualifications.
Therefore, evaluating whether LLMs can provide accurate information is essential to ensure their reliability in practical applications within these fields.
In this study, we first prepared and published a dataset of Q&As from the business law section of the multiple-choice format of the Japanese CPA examination. We then used the ChatGPT API to evaluate its response capabilities. This allowed us to understand the response abilities and limitations of language models in challenging professional certification exams.
Keyword (in Japanese) (See Japanese page) 
(in English) CPA Examination / Large Language Models / Corporate Law / ChatGPT / / / /  
Reference Info. IEICE Tech. Rep., vol. 124, no. 173, NLC2024-6, pp. 27-32, Sept. 2024.
Paper # NLC2024-6 
Date of Issue 2024-08-26 (NLC) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
reproduction
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF NLC2024-6

Conference Information
Committee NLC  
Conference Date 2024-09-02 - 2024-09-03 
Place (in Japanese) (See Japanese page) 
Place (in English) Hokkaido University. The Clark Memorial Student Center. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) The 21st Text Analytics Symposium 
Paper Information
Registration To NLC 
Conference Code 2024-09-NLC 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Performance Analysis of ChatGPT in Solving the CPA Multiple-Choice Exam (Business Law) 
Sub Title (in English)  
Keyword(1) CPA Examination  
Keyword(2) Large Language Models  
Keyword(3) Corporate Law  
Keyword(4) ChatGPT  
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Keyword(6)  
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1st Author's Name Tatsuki Masuda  
1st Author's Affiliation Keio University/RIKEN Center for AIP (Keio Univ./RIKEN AIP)
2nd Author's Name Kei Nakagawa  
2nd Author's Affiliation Nomura Asset Management Co., Ltd./Osaka Metropolitan University (Nomura Asset Management/Osaka Metropolitan Univ.)
3rd Author's Name Kaito Takano  
3rd Author's Affiliation Nomura Asset Management Co., Ltd. (Nomura Asset Management)
4th Author's Name Takahiro Hoshino  
4th Author's Affiliation Keio University/RIKEN Center for AIP (Keio Univ./RIKEN AIP)
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Speaker Author-1 
Date Time 2024-09-02 15:10:00 
Presentation Time 20 minutes 
Registration for NLC 
Paper # NLC2024-6 
Volume (vol) vol.124 
Number (no) no.173 
Page pp.27-32 
#Pages
Date of Issue 2024-08-26 (NLC) 


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