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Paper Abstract and Keywords
Presentation 2026-03-13 13:55
An Empirical Analysis of Contextual Memory Reconstruction in Generative AI
Toshiaki Kawagoshi, Takayoshi Otsuki, Kazuki Yamamoto, Shota Yano, Naoto Hoshikawa (Tsukuba Univ.) SC2025-42
Abstract (in Japanese) (See Japanese page) 
(in English) This study builds on an evaluation framework developed in a graduate PBL course and restructures it for research purposes, comparing a manual evaluation in an interactive UI with an API-based reproduction to examine how observation conditions affect contextual responses of generative AI services. The difficulty structure was largely reproduced. However, API-based scores showed reduced variance and a shift toward higher ratings for OpenAI/Gemini/Azure, whereas Claude scored lower in several context-dependent categories, including family information and social media accounts. These results suggest that “contextual memory” is better understood as reconstruction rather than static storage and provide implications for service selection and prompt design.
Keyword (in Japanese) (See Japanese page) 
(in English) Generative AI / Contextual Memory / Information Reconstruction / Interactive UI / API-based Reproduction / Interaction Effects / Evaluation Framework /  
Reference Info. IEICE Tech. Rep., vol. 125, no. 400, SC2025-42, pp. 12-17, March 2026.
Paper # SC2025-42 
Date of Issue 2026-03-06 (SC) 
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 SC2025-42

Conference Information
Committee SC  
Conference Date 2026-03-13 - 2026-03-14 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To SC 
Conference Code 2026-03-SC 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) An Empirical Analysis of Contextual Memory Reconstruction in Generative AI 
Sub Title (in English)  
Keyword(1) Generative AI  
Keyword(2) Contextual Memory  
Keyword(3) Information Reconstruction  
Keyword(4) Interactive UI  
Keyword(5) API-based Reproduction  
Keyword(6) Interaction Effects  
Keyword(7) Evaluation Framework  
Keyword(8)  
1st Author's Name Toshiaki Kawagoshi  
1st Author's Affiliation Graduate School of Science and Technology, University of Tsukuba (Tsukuba Univ.)
2nd Author's Name Takayoshi Otsuki  
2nd Author's Affiliation Graduate School of Science and Technology, University of Tsukuba (Tsukuba Univ.)
3rd Author's Name Kazuki Yamamoto  
3rd Author's Affiliation Graduate School of Science and Technology, University of Tsukuba (Tsukuba Univ.)
4th Author's Name Shota Yano  
4th Author's Affiliation Graduate School of Science and Technology, University of Tsukuba (Tsukuba Univ.)
5th Author's Name Naoto Hoshikawa  
5th Author's Affiliation Graduate School of Science and Technology, University of Tsukuba (Tsukuba Univ.)
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Speaker Author-1 
Date Time 2026-03-13 13:55:00 
Presentation Time 25 minutes 
Registration for SC 
Paper # SC2025-42 
Volume (vol) vol.125 
Number (no) no.400 
Page pp.12-17 
#Pages 6 
Date of Issue 2026-03-06 (SC) 

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