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Paper Abstract and Keywords
Presentation 2024-09-02 14:50
An Investigation into the Impact of Model Scale and Quantization Precision on the Performance of Local Large Language Models -- Applications in Sentiment Analysis of Online Reviews for Restaurant Evaluations --
Junichiro Niimi (Meijo Univ.) NLC2024-5
Abstract (in Japanese) (See Japanese page) 
(in English) It has become common for consumers to post texts online, such as opinions and product reviews. Various methods to analyze these data have been explored in the field of natural language processing. Recently, large language models (LLMs) are actively utilized. While many commercially available LLMs are provided as cloud services, the demand for local LLMs is increasing due to privacy and data concerns. To execute them locally, parameter quantization is necessary; however, the relationship between the number of parameters, number of bits in quantization, and the accuracy of LLMs remains unclear. Therefore, this study aims to construct multiple sentiment analysis models for electronic word-of-mouth (eWOM) and explore the optimal model for practical use.
Keyword (in Japanese) (See Japanese page) 
(in English) sentiment analysis / electronic word-of-mouth / large language model / quantization / / / /  
Reference Info. IEICE Tech. Rep., vol. 124, no. 173, NLC2024-5, pp. 21-26, Sept. 2024.
Paper # NLC2024-5 
Date of Issue 2024-08-26 (NLC) 
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 NLC2024-5

Conference Information
Committee NLC  
Conference Date 2024-09-02 - 2024-09-03 
Place (in Japanese) (See Japanese page) 
Place (in English) Hokkaido University. The Clark Memorial Student Center. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) The 21st Text Analytics Symposium 
Paper Information
Registration To NLC 
Conference Code 2024-09-NLC 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) An Investigation into the Impact of Model Scale and Quantization Precision on the Performance of Local Large Language Models 
Sub Title (in English) Applications in Sentiment Analysis of Online Reviews for Restaurant Evaluations 
Keyword(1) sentiment analysis  
Keyword(2) electronic word-of-mouth  
Keyword(3) large language model  
Keyword(4) quantization  
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1st Author's Name Junichiro Niimi  
1st Author's Affiliation Meijo University (Meijo Univ.)
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Speaker Author-1 
Date Time 2024-09-02 14:50:00 
Presentation Time 20 minutes 
Registration for NLC 
Paper # NLC2024-5 
Volume (vol) vol.124 
Number (no) no.173 
Page pp.21-26 
#Pages 6 
Date of Issue 2024-08-26 (NLC) 

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