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Paper Abstract and Keywords
Presentation 2026-03-05 11:25
Methods for Generating Clues to Support Voluntary Examination of Risky Factors in AI-Generated Documents
Shogo Uchida, Ryo Onuma, Hiroki Nakayama, Hiroaki Kaminaga (Fukushima Univ.), Youzou Miyadera (Gakugei Univ.), Shoichi Nakamura (Fukushima Univ.) ET2025-78
Abstract (in Japanese) (See Japanese page) 
(in English) With the rapid spread of generative AI, there is an urgent need to train users in its ability to utilize it. Generative AI leverages vast amounts of information on the internet as training data, offering users the advantage of easily acquiring information. However, AI-generated documents may contain descriptions whose authenticities or sources are uncertain, posing risks that cannot be overlooked. Although users should be aware of and verify the dangerous factors in AI-generated documents by themselves, it is not easy for inexperienced users to find and examine such factors. In this research, we have aimed to develop methods of generating clues for exercises in which users voluntarily examine the risky factors that require attention in AI-generated documents. In this paper, we initially tidy factors to verify (i.e., precarious descriptions in AI-generated documents). We then describe methods for estimating those descriptions that may be misinformation and whose sources are unclear. Furthermore, we provide an overview of the support system based on these methods and describe the support for examination of risky factors.
Keyword (in Japanese) (See Japanese page) 
(in English) Reliability of AI-generated documents / Risky factors / Authenticity verification support / Source of AI-generated output / Generative AI / / /  
Reference Info. IEICE Tech. Rep., vol. 125, no. 391, ET2025-78, pp. 118-123, March 2026.
Paper # ET2025-78 
Date of Issue 2026-02-25 (ET) 
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 ET2025-78

Conference Information
Committee ET  
Conference Date 2026-03-04 - 2026-03-05 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To ET 
Conference Code 2026-03-ET 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Methods for Generating Clues to Support Voluntary Examination of Risky Factors in AI-Generated Documents 
Sub Title (in English)  
Keyword(1) Reliability of AI-generated documents  
Keyword(2) Risky factors  
Keyword(3) Authenticity verification support  
Keyword(4) Source of AI-generated output  
Keyword(5) Generative AI  
Keyword(6)  
Keyword(7)  
Keyword(8)  
1st Author's Name Shogo Uchida  
1st Author's Affiliation Fukushima University (Fukushima Univ.)
2nd Author's Name Ryo Onuma  
2nd Author's Affiliation Fukushima University (Fukushima Univ.)
3rd Author's Name Hiroki Nakayama  
3rd Author's Affiliation Fukushima University (Fukushima Univ.)
4th Author's Name Hiroaki Kaminaga  
4th Author's Affiliation Fukushima University (Fukushima Univ.)
5th Author's Name Youzou Miyadera  
5th Author's Affiliation Tokyo Gakugei University (Gakugei Univ.)
6th Author's Name Shoichi Nakamura  
6th Author's Affiliation Fukushima University (Fukushima Univ.)
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Speaker Author-1 
Date Time 2026-03-05 11:25:00 
Presentation Time 25 minutes 
Registration for ET 
Paper # ET2025-78 
Volume (vol) vol.125 
Number (no) no.391 
Page pp.118-123 
#Pages 6 
Date of Issue 2026-02-25 (ET) 

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