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Paper Abstract and Keywords
Presentation 2026-02-19 10:30
A Rationale-Guided and Rule-Based LLM Framework for Analyzing Psychological Counseling Dialogues
Zhihao Shao (UTokyo), Ryo Sekizaki (WelcomeToTalk), Shengzhou Yi, Toshihiko Yamasaki (UTokyo) ITS2025-42 IE2025-57
Abstract (in Japanese) (See Japanese page) 
(in English) This study focuses on the automatic severity assessment of student counseling dialogues, where the input consists of counseling records written by students and the output is a psychological risk label~(low risk or high risk) together with the rationale for the prediction. Existing large language model–based approaches often rely on surface-level emotional cues, exhibit unstable reasoning, and lack transparent links between evidence and decisions. To address these issues, we propose a rationale-guided and rule-based framework that integrates rationale generation with rule-driven self-improvement. Before prediction, the system generates and contrasts paired rationales for both possible labels to clarify evidence usage and decision boundaries. After prediction, misclassified samples are analyzed to automatically extract interpretable rules and representative error examples, which are then incorporated as guidance and constraints for subsequent predictions. Experiments are conducted on 6,481 real counseling records collected from the Welcome to Talk online psychological counseling platform, annotated by trained volunteers and stratified into training, validation, and test sets under a binary risk scheme. Results show that our method achieves the best performance among the evaluated methods~(0.911) and MCC~(0.541), outperforming multiple strong baselines. The performance improvement arises from the synergy between rationale guidance and rule-based reflection, enhancing evidence alignment, boundary discrimination, and error suppression.
Keyword (in Japanese) (See Japanese page) 
(in English) Mental Health Classification / Large Language Models / Self-Reflection / Rationale-Guided Reasoning / / / /  
Reference Info. IEICE Tech. Rep., vol. 125, no. 356, IE2025-57, pp. 13-18, Feb. 2026.
Paper # IE2025-57 
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 ITS2025-42 IE2025-57

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 English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Rationale-Guided and Rule-Based LLM Framework for Analyzing Psychological Counseling Dialogues 
Sub Title (in English)  
Keyword(1) Mental Health Classification  
Keyword(2) Large Language Models  
Keyword(3) Self-Reflection  
Keyword(4) Rationale-Guided Reasoning  
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1st Author's Name Zhihao Shao  
1st Author's Affiliation The University of Tokyo (UTokyo)
2nd Author's Name Ryo Sekizaki  
2nd Author's Affiliation Welcome to talk Co. Ltd. (WelcomeToTalk)
3rd Author's Name Shengzhou Yi  
3rd Author's Affiliation The University of Tokyo (UTokyo)
4th Author's Name Toshihiko Yamasaki  
4th Author's Affiliation The University of Tokyo (UTokyo)
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Speaker Author-1 
Date Time 2026-02-19 10:30:00 
Presentation Time 15 minutes 
Registration for IE 
Paper # ITS2025-42, IE2025-57 
Volume (vol) vol.125 
Number (no) no.355(ITS), no.356(IE) 
Page pp.13-18 
#Pages 6 
Date of Issue 2026-02-12 (ITS, IE) 

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