Advancing Cross-Lingual Aspect-Based Sentiment Analysis with LLMs and Constrained Decoding for Sequence-to-Sequence Models
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F25%3A43975483" target="_blank" >RIV/49777513:23520/25:43975483 - isvavai.cz</a>
Result on the web
<a href="https://www.scitepress.org/PublicationsDetail.aspx?ID=XPUs7tfQdCI=&t=1" target="_blank" >https://www.scitepress.org/PublicationsDetail.aspx?ID=XPUs7tfQdCI=&t=1</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.5220/0013349400003890" target="_blank" >10.5220/0013349400003890</a>
Alternative languages
Result language
angličtina
Original language name
Advancing Cross-Lingual Aspect-Based Sentiment Analysis with LLMs and Constrained Decoding for Sequence-to-Sequence Models
Original language description
Aspect-based sentiment analysis (ABSA) has made significant strides, yet challenges remain for low-resource languages due to the predominant focus on English. Current cross-lingual ABSA studies often centre on simpler tasks and rely heavily on external translation tools. In this paper, we present a novel sequence-to sequence method for compound ABSA tasks that eliminates the need for such tools. Our approach, which uses constrained decoding, improves cross-lingual ABSA performance by up to 10%. This method broadens the scope of cross-lingual ABSA, enabling it to handle more complex tasks and providing a practical, efficient alternative to translation-dependent techniques. Furthermore, we compare our approach with large language models (LLMs) and show that while fine-tuned multilingual LLMs can achieve comparable results, English centric LLMs struggle with these tasks.
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/EH23_021%2F0008436" target="_blank" >EH23_021/0008436: RandD of technologies for advanced digitization in the Pilsen metropolitan area (DigiTech)</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART
ISBN
978-989-758-737-5
ISSN
2184-433X
e-ISSN
—
Number of pages
10
Pages from-to
757-766
Publisher name
ScitePress
Place of publication
Setúbal
Event location
Porto
Event date
Feb 23, 2025
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
—