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Paper Abstract and Keywords
Presentation 2026-02-19 12:00
A Dataset for Evaluating Ingredient State Understanding in Cooking Videos
Mashiro Toyooka, Yoko Yamakata (UT) ITS2025-47 IE2025-62
Abstract (in Japanese) (See Japanese page) 
(in English) In this paper, we investigate a method for constructing an ingredient state graph dataset from cooking videos, as well as an evaluation framework for assessing ingredient state understanding using this dataset.
Our approach leverages large language models with strong textual understanding to generate ingredient state graphs that represent transitions of ingredient states from cooking videos annotated with text, using a method that is robust to noise.
In addition, we generate a set of questions for each ingredient that query its state, and represent state transitions by tracking how the responses to these questions change over time.
The proposed evaluation framework enables quantitative evaluation of ingredient states described in an open-vocabulary and free-form manner, which is suitable for the era of large multimodal models.
Keyword (in Japanese) (See Japanese page) 
(in English) Large Multimodal Model / State Estimation / Real-world Understanding / Cooking Video / / / /  
Reference Info. IEICE Tech. Rep., vol. 125, no. 356, IE2025-62, pp. 43-48, Feb. 2026.
Paper # IE2025-62 
Date of Issue 2026-02-12 (ITS, IE) 
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 ITS2025-47 IE2025-62

Conference Information
Committee IE ITS ITE-MMS ITE-ME ITE-AIT ITE-SIP  
Conference Date 2026-02-19 - 2026-02-20 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To IE 
Conference Code 2026-02-IE-ITS-MMS-ME-AIT-SIP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Dataset for Evaluating Ingredient State Understanding in Cooking Videos 
Sub Title (in English)  
Keyword(1) Large Multimodal Model  
Keyword(2) State Estimation  
Keyword(3) Real-world Understanding  
Keyword(4) Cooking Video  
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1st Author's Name Mashiro Toyooka  
1st Author's Affiliation The University of Tokyo (UT)
2nd Author's Name Yoko Yamakata  
2nd Author's Affiliation The University of Tokyo (UT)
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Speaker Author-1 
Date Time 2026-02-19 12:00:00 
Presentation Time 15 minutes 
Registration for IE 
Paper # ITS2025-47, IE2025-62 
Volume (vol) vol.125 
Number (no) no.355(ITS), no.356(IE) 
Page pp.43-48 
#Pages 6 
Date of Issue 2026-02-12 (ITS, IE) 

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