Pseudo-Semantic Graphs for Generating Paraphrases
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F26%3AE5QZUZ6F" target="_blank" >RIV/00216208:11320/26:E5QZUZ6F - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-031-73503-5_18" target="_blank" >http://dx.doi.org/10.1007/978-3-031-73503-5_18</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-73503-5_18" target="_blank" >10.1007/978-3-031-73503-5_18</a>
Alternative languages
Result language
angličtina
Original language name
Pseudo-Semantic Graphs for Generating Paraphrases
Original language description
Paraphrases are texts written using different words but conveying the same meaning; hence, their quality is based upon retaining semantics while varying syntax/vocabulary. Recent works leverage structured syntactic information to control the syntax of the generations while relying on pretrained language models to retain the semantics. However, rarely do works in the literature consider using structured semantic information to enrich the language representation. In this work, we propose to model the task of paraphrase generation as a pseudo-Graph-to-Text task where we fine-tune pretrained language models using as input linearized representations of pseudo-semantic graphs built from dependency parsing trees sourced from the original input texts. Our model achieves competitive results on three popular paraphrase generation benchmarks. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
Czech name
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Czech description
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Classification
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)
Result continuities
Project
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Continuities
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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
Lect. Notes Comput. Sci.
ISBN
978-3-031-73502-8
ISSN
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e-ISSN
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Number of pages
13
Pages from-to
215-227
Publisher name
Springer Science and Business Media Deutschland GmbH
Place of publication
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Event location
Viana do Castelo
Event date
Jan 1, 2026
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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