Zero-shot Cross-lingual Automated Essay Scoring

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3ABR2L9BYM" target="_blank" >RIV/00216208:11320/25:BR2L9BYM - isvavai.cz</a>

Result on the web

<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195944109&partnerID=40&md5=fe5da350aae64a5bab7ffeb57bacab65" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195944109&partnerID=40&md5=fe5da350aae64a5bab7ffeb57bacab65</a>

DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Zero-shot Cross-lingual Automated Essay Scoring

Original language description

Due to the difficulty of creating high-quality labelled training data for different languages, the low-resource problem is crucial yet challenging for automated essay scoring (AES). However, little attention has been paid to addressing this challenge. In this paper, we propose a novel zero-shot cross-lingual scoring method from the perspectives of pretrained multilingual representation and writing quality alignment to score essays in unseen languages. Specifically, we adopt multilingual pretrained language models as the encoder backbone to deeply and comprehensively represent multilingual essays. Motivated by the fact that the scoring knowledge for evaluating writing quality is comparable across different languages, we introduce an innovative strategy for aligning essays in a language-independent manner. The proposed strategy aims to capture shared knowledge from diverse languages, thereby enhancing the representation of essays written in unseen languages with respect to their quality. We include essay datasets in six languages (Czech, German, English, Spanish, Italian and Portuguese) to establish extensive experiments, and the results demonstrate that our method achieves state-of-the-art cross-lingual scoring performance. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

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Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Jt. Int. Conf. Comput. Linguist., Lang. Resour. Eval., LREC-COLING - Main Conf. Proc.

ISBN

978-249381410-4

ISSN

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e-ISSN

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Number of pages

14

Pages from-to

17819-17832

Publisher name

European Language Resources Association (ELRA)

Place of publication

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Event location

Torino, Italia

Event date

Jan 1, 2025

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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