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Paper Abstract and Keywords
Presentation 2026-03-18 09:20
Iterative Evaluation and Improvement Framework for Real Estate Rent Prediction Models Using Large Language Models
Yuta Takatsuji (The Univ. of Tokyo), Tatsuya Iwanari, Ryosuke Katsuta (estie), Shuntaro Masuda, Shengzhou Yi, Toshihiko Yamasaki (The Univ. of Tokyo) IMQ2025-97 IE2025-174 MVE2025-104
Abstract (in Japanese) (See Japanese page) 
(in English) Improving the accuracy of machine learning models for real estate rent prediction requires expert-level trial and error as well as significant labor. Although research on automation using Large Language Models (LLMs) has advanced in recent years, most existing methods are limited to specific stages such as feature engineering, and investigations focused on rent prediction tasks remain insufficient. We propose an iterative improvement framework that leverages the prior knowledge and reasoning capabilities of LLMs to automatically cycle through the planning, implementation, and evaluation of improvement strategies integrating multiple methodologies. By providing feedback on past trial histories and detailed error information, the framework enables the LLM to efficiently explore promising improvement proposals. Validation using a nationwide rental housing dataset confirmed a statistically significant improvement in accuracy compared to a baseline LightGBM model, demonstrating a stepwise performance enhancement corresponding to the number of iterations.
Keyword (in Japanese) (See Japanese page) 
(in English) Real Estate Rent Prediction / Large Language Model / Automated Machine Learning / / / / /  
Reference Info. IEICE Tech. Rep., vol. 125, no. 411, MVE2025-104, pp. 430-435, March 2026.
Paper # MVE2025-104 
Date of Issue 2026-03-09 (IMQ, IE, MVE) 
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 IMQ2025-97 IE2025-174 MVE2025-104

Conference Information
Committee CQ MVE IMQ IE  
Conference Date 2026-03-16 - 2026-03-18 
Place (in Japanese) (See Japanese page) 
Place (in English) Okinawa-Sangyoushien-Center 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To MVE 
Conference Code 2026-03-CQ-MVE-IMQ-IE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Iterative Evaluation and Improvement Framework for Real Estate Rent Prediction Models Using Large Language Models 
Sub Title (in English)  
Keyword(1) Real Estate Rent Prediction  
Keyword(2) Large Language Model  
Keyword(3) Automated Machine Learning  
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1st Author's Name Yuta Takatsuji  
1st Author's Affiliation The University of Tokyo (The Univ. of Tokyo)
2nd Author's Name Tatsuya Iwanari  
2nd Author's Affiliation estie, inc. (estie)
3rd Author's Name Ryosuke Katsuta  
3rd Author's Affiliation estie, inc. (estie)
4th Author's Name Shuntaro Masuda  
4th Author's Affiliation The University of Tokyo (The Univ. of Tokyo)
5th Author's Name Shengzhou Yi  
5th Author's Affiliation The University of Tokyo (The Univ. of Tokyo)
6th Author's Name Toshihiko Yamasaki  
6th Author's Affiliation The University of Tokyo (The Univ. of Tokyo)
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Speaker Author-1 
Date Time 2026-03-18 09:20:00 
Presentation Time 20 minutes 
Registration for MVE 
Paper # IMQ2025-97, IE2025-174, MVE2025-104 
Volume (vol) vol.125 
Number (no) no.408(IMQ), no.410(IE), no.411(MVE) 
Page pp.430-435 
#Pages 6 
Date of Issue 2026-03-09 (IMQ, IE, MVE) 

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