Contemporary LLMs and Literary Abridgement: An Analytical Inquiry
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3A9S4B55QJ" target="_blank" >RIV/00216208:11320/25:9S4B55QJ - isvavai.cz</a>
Výsledek na webu
<a href="https://aclanthology.org/2024.clib-1.4" target="_blank" >https://aclanthology.org/2024.clib-1.4</a>
DOI - Digital Object Identifier
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Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Contemporary LLMs and Literary Abridgement: An Analytical Inquiry
Popis výsledku v původním jazyce
Within the framework of this study, several contemporary Large Language Models (ChatGPT, Gemini Pro, Mistral-Instruct and BgGPT) are evaluated in relation to their ability to generate abridged versions of literary texts. The analysis is based on 'The Ugly Duckling' by H. C. Andersen as translated into English, French and Bulgarian. The different scenarios of abridgement experimented with include zero-shot, one-shot, division into chunks and crosslingual (including chain-of-thought) abridgement. The resulting texts are evaluated both automatically and via human evaluation. The automatic analysis includes ROUGE and BERTScore as well as the ratios of a selection of readability-related textual features (e.g. number of words, type-to-token ratio) as pertaining to the original versus automatically abridged texts. Professionally composed abridged versions are regarded as gold standard. Following the automatic analysis, six selected best candidate texts per language are then evaluated by volunteers with university education in terms of textual characteristics of a more qualitative nature, such as coherence, consistency and aesthetic appeal.
Název v anglickém jazyce
Contemporary LLMs and Literary Abridgement: An Analytical Inquiry
Popis výsledku anglicky
Within the framework of this study, several contemporary Large Language Models (ChatGPT, Gemini Pro, Mistral-Instruct and BgGPT) are evaluated in relation to their ability to generate abridged versions of literary texts. The analysis is based on 'The Ugly Duckling' by H. C. Andersen as translated into English, French and Bulgarian. The different scenarios of abridgement experimented with include zero-shot, one-shot, division into chunks and crosslingual (including chain-of-thought) abridgement. The resulting texts are evaluated both automatically and via human evaluation. The automatic analysis includes ROUGE and BERTScore as well as the ratios of a selection of readability-related textual features (e.g. number of words, type-to-token ratio) as pertaining to the original versus automatically abridged texts. Professionally composed abridged versions are regarded as gold standard. Following the automatic analysis, six selected best candidate texts per language are then evaluated by volunteers with university education in terms of textual characteristics of a more qualitative nature, such as coherence, consistency and aesthetic appeal.
Klasifikace
Druh
D - Stať ve sborníku
CEP obor
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OECD FORD obor
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Návaznosti výsledku
Projekt
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Návaznosti
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Ostatní
Rok uplatnění
2024
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název statě ve sborníku
Proceedings of the Sixth International Conference on Computational Linguistics in Bulgaria (CLIB 2024)
ISBN
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ISSN
2367-5578
e-ISSN
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Počet stran výsledku
19
Strana od-do
39-57
Název nakladatele
Department of Computational Linguistics, Institute for Bulgarian Language, Bulgarian Academy of Sciences
Místo vydání
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Místo konání akce
Sofia, Bulgaria
Datum konání akce
1. 1. 2025
Typ akce podle státní příslušnosti
WRD - Celosvětová akce
Kód UT WoS článku
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