Publicação
Exploring few-shot approaches to automatic text complexity assessment in european portuguese
| datacite.subject.sdg | 04:Educação de Qualidade | |
| datacite.subject.sdg | 09:Indústria, Inovação e Infraestruturas | |
| datacite.subject.sdg | 10:Reduzir as Desigualdades | |
| dc.contributor.author | Ribeiro, Eugénio | |
| dc.contributor.author | Antunes, David | |
| dc.contributor.author | Mamede, Nuno | |
| dc.contributor.author | Baptista, Jorge | |
| dc.date.accessioned | 2026-04-29T10:17:02Z | |
| dc.date.available | 2026-04-29T10:17:02Z | |
| dc.date.issued | 2025-08-21 | |
| dc.description.abstract | The automatic assessment of text complexity has an important role to play in the context of language education. In this study, we shift the focus from L2 learners to adult native speakers with low literacy by exploring the new iRead4Skills dataset in European Portuguese. Furthermore, instead of relying on classical machine learning approaches or fine-tuning a pre-trained language model, we leverage the capabilities of prompt-based Large Language Models (LLMs), with a special focus on few-shot prompting approaches. We explore prompts with varying degrees of information, as well as different example selection approaches. Overall, the results of our experiments reveal that even a single example significantly increases the performance of the model and that few-shot approaches generalize better than fine-tuned models. However, automatic complexity assessment is a difficult and highly subjective task that is still far from solved. | eng |
| dc.identifier.doi | 10.5753/jbcs.2025.5820 | |
| dc.identifier.issn | 1678-4804 | |
| dc.identifier.uri | http://hdl.handle.net/10400.1/28799 | |
| dc.language.iso | eng | |
| dc.peerreviewed | yes | |
| dc.publisher | Brazilian Computer Society (SBC) | |
| dc.relation | Instituto de Engenharia de Sistemas e Computadores, Investigação e Desenvolvimento em Lisboa | |
| dc.relation.ispartof | Journal of the Brazilian Computer Society | |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | Text complexity | |
| dc.subject | Readability | |
| dc.subject | Few-shot prompting | |
| dc.subject | Large language models | |
| dc.title | Exploring few-shot approaches to automatic text complexity assessment in european portuguese | eng |
| dc.type | journal article | |
| dspace.entity.type | Publication | |
| oaire.awardNumber | UIDB/50021/2020 | |
| oaire.awardTitle | Instituto de Engenharia de Sistemas e Computadores, Investigação e Desenvolvimento em Lisboa | |
| oaire.awardURI | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F50021%2F2020/PT | |
| oaire.citation.endPage | 710 | |
| oaire.citation.issue | 1 | |
| oaire.citation.startPage | 690 | |
| oaire.citation.title | Journal of the Brazilian Computer Society | |
| oaire.citation.volume | 31 | |
| oaire.fundingStream | 6817 - DCRRNI ID | |
| oaire.version | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |
| person.familyName | Baptista | |
| person.givenName | Jorge | |
| person.identifier.ciencia-id | 7010-5366-22C5 | |
| person.identifier.orcid | 0000-0003-4603-4364 | |
| person.identifier.rid | H-7699-2013 | |
| person.identifier.scopus-author-id | 14035269500 | |
| project.funder.identifier | http://doi.org/10.13039/501100001871 | |
| project.funder.name | Fundação para a Ciência e a Tecnologia | |
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