@inproceedings{paszkowska-2025-instruction,
title = "Instruction fine-tuning using pragmatic layer",
author = "Paszkowska, Adrianna",
editor = "Kobyli{\'n}ski, {\L}ukasz and
Wr{\'o}blewska, Alina and
Ogrodniczuk, Maciej",
booktitle = "Proceedings of the {P}ol{E}val 2025 Workshop",
month = nov,
year = "2025",
address = "Warsaw",
publisher = "Institute of Computer Science PAS and Association for Computational Linguistics",
url = "https://aclanthology.org/2025.poleval-main.9/",
pages = "60--65",
abstract = "The Polish language, like some Slavic and Romance languages, has a masculine-centric bias in its generic forms, leading to frequent use of masculine nouns when referring to women or mixed-gender groups. This presents a linguistic challenge for development of gender-inclusive technologies, addressed in PolEval task 2.This paper presents pragmatic instruction fine-tuning approach, using Low-Rank Adaptation (LoRA) on the pre-trained Polish PLT5 sequence-to-sequence model."
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<abstract>The Polish language, like some Slavic and Romance languages, has a masculine-centric bias in its generic forms, leading to frequent use of masculine nouns when referring to women or mixed-gender groups. This presents a linguistic challenge for development of gender-inclusive technologies, addressed in PolEval task 2.This paper presents pragmatic instruction fine-tuning approach, using Low-Rank Adaptation (LoRA) on the pre-trained Polish PLT5 sequence-to-sequence model.</abstract>
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%0 Conference Proceedings
%T Instruction fine-tuning using pragmatic layer
%A Paszkowska, Adrianna
%Y Kobyliński, Łukasz
%Y Wróblewska, Alina
%Y Ogrodniczuk, Maciej
%S Proceedings of the PolEval 2025 Workshop
%D 2025
%8 November
%I Institute of Computer Science PAS and Association for Computational Linguistics
%C Warsaw
%F paszkowska-2025-instruction
%X The Polish language, like some Slavic and Romance languages, has a masculine-centric bias in its generic forms, leading to frequent use of masculine nouns when referring to women or mixed-gender groups. This presents a linguistic challenge for development of gender-inclusive technologies, addressed in PolEval task 2.This paper presents pragmatic instruction fine-tuning approach, using Low-Rank Adaptation (LoRA) on the pre-trained Polish PLT5 sequence-to-sequence model.
%U https://aclanthology.org/2025.poleval-main.9/
%P 60-65
Markdown (Informal)
[Instruction fine-tuning using pragmatic layer](https://aclanthology.org/2025.poleval-main.9/) (Paszkowska, PolEval 2025)
ACL