Standard
MultiLS: An End-to-End Lexical Simplification Framework. / North, Kai
; Ranasinghe, Tharindu; Shardlow, Matthew et al.
Proceedings of the Third Workshop on Text Simplification, Accessibility and Readability (TSAR 2024). ed. / Matthew Shardlow; Horacio Saggion; Fernando Alva-Manchego; Marcos Zampieri; Kai North; Sanja Štajner; Regina Stodden. Kerrville: Association for Computational Linguistics (ACL Anthology), 2024. p. 1-11.
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Harvard
North, K
, Ranasinghe, T, Shardlow, M & Zampieri, M 2024,
MultiLS: An End-to-End Lexical Simplification Framework. in M Shardlow, H Saggion, F Alva-Manchego, M Zampieri, K North, S Štajner & R Stodden (eds),
Proceedings of the Third Workshop on Text Simplification, Accessibility and Readability (TSAR 2024). Association for Computational Linguistics (ACL Anthology), Kerrville, pp. 1-11, Third Workshop on Text Simplification, Accessibility and Readability,
15/11/24.
https://doi.org/10.18653/v1/2024.tsar-1.1APA
North, K.
, Ranasinghe, T., Shardlow, M., & Zampieri, M. (2024).
MultiLS: An End-to-End Lexical Simplification Framework. In M. Shardlow, H. Saggion, F. Alva-Manchego, M. Zampieri, K. North, S. Štajner, & R. Stodden (Eds.),
Proceedings of the Third Workshop on Text Simplification, Accessibility and Readability (TSAR 2024) (pp. 1-11). Association for Computational Linguistics (ACL Anthology).
https://doi.org/10.18653/v1/2024.tsar-1.1Vancouver
North K
, Ranasinghe T, Shardlow M, Zampieri M.
MultiLS: An End-to-End Lexical Simplification Framework. In Shardlow M, Saggion H, Alva-Manchego F, Zampieri M, North K, Štajner S, Stodden R, editors, Proceedings of the Third Workshop on Text Simplification, Accessibility and Readability (TSAR 2024). Kerrville: Association for Computational Linguistics (ACL Anthology). 2024. p. 1-11 doi: 10.18653/v1/2024.tsar-1.1
Author
North, Kai
; Ranasinghe, Tharindu ; Shardlow, Matthew et al. /
MultiLS : An End-to-End Lexical Simplification Framework. Proceedings of the Third Workshop on Text Simplification, Accessibility and Readability (TSAR 2024). editor / Matthew Shardlow ; Horacio Saggion ; Fernando Alva-Manchego ; Marcos Zampieri ; Kai North ; Sanja Štajner ; Regina Stodden. Kerrville : Association for Computational Linguistics (ACL Anthology), 2024. pp. 1-11
Bibtex
@inproceedings{a7c5fe51dbe242df8170a33765895d18,
title = "MultiLS: An End-to-End Lexical Simplification Framework",
abstract = "Lexical Simplification (LS) automatically replaces difficult to read words for easier alternatives while preserving a sentence{\textquoteright}s original meaning. Several datasets exist for LS and each of them specialize in one or two sub-tasks within the LS pipeline. However, as of this moment, no single LS dataset has been developed that covers all LS sub-tasks. We present MultiLS, the first LS framework that allows for the creation of a multi-task LS dataset. We also present MultiLS-PT, the first dataset created using the MultiLS framework. We demonstrate the potential of MultiLS-PT by carrying out all LS sub-tasks of (1) lexical complexity prediction (LCP), (2) substitute generation, and (3) substitute ranking for Portuguese.",
author = "Kai North and Tharindu Ranasinghe and Matthew Shardlow and Marcos Zampieri",
year = "2024",
month = nov,
day = "15",
doi = "10.18653/v1/2024.tsar-1.1",
language = "English",
pages = "1--11",
editor = "Matthew Shardlow and Horacio Saggion and Fernando Alva-Manchego and Marcos Zampieri and Kai North and Sanja {\v S}tajner and Regina Stodden",
booktitle = "Proceedings of the Third Workshop on Text Simplification, Accessibility and Readability (TSAR 2024)",
publisher = "Association for Computational Linguistics (ACL Anthology)",
note = "Third Workshop on Text Simplification, Accessibility and Readability : TSAR ; Conference date: 15-11-2024",
}
RIS
TY - GEN
T1 - MultiLS
T2 - Third Workshop on Text Simplification, Accessibility and Readability
AU - North, Kai
AU - Ranasinghe, Tharindu
AU - Shardlow, Matthew
AU - Zampieri, Marcos
PY - 2024/11/15
Y1 - 2024/11/15
N2 - Lexical Simplification (LS) automatically replaces difficult to read words for easier alternatives while preserving a sentence’s original meaning. Several datasets exist for LS and each of them specialize in one or two sub-tasks within the LS pipeline. However, as of this moment, no single LS dataset has been developed that covers all LS sub-tasks. We present MultiLS, the first LS framework that allows for the creation of a multi-task LS dataset. We also present MultiLS-PT, the first dataset created using the MultiLS framework. We demonstrate the potential of MultiLS-PT by carrying out all LS sub-tasks of (1) lexical complexity prediction (LCP), (2) substitute generation, and (3) substitute ranking for Portuguese.
AB - Lexical Simplification (LS) automatically replaces difficult to read words for easier alternatives while preserving a sentence’s original meaning. Several datasets exist for LS and each of them specialize in one or two sub-tasks within the LS pipeline. However, as of this moment, no single LS dataset has been developed that covers all LS sub-tasks. We present MultiLS, the first LS framework that allows for the creation of a multi-task LS dataset. We also present MultiLS-PT, the first dataset created using the MultiLS framework. We demonstrate the potential of MultiLS-PT by carrying out all LS sub-tasks of (1) lexical complexity prediction (LCP), (2) substitute generation, and (3) substitute ranking for Portuguese.
U2 - 10.18653/v1/2024.tsar-1.1
DO - 10.18653/v1/2024.tsar-1.1
M3 - Conference contribution/Paper
SP - 1
EP - 11
BT - Proceedings of the Third Workshop on Text Simplification, Accessibility and Readability (TSAR 2024)
A2 - Shardlow, Matthew
A2 - Saggion, Horacio
A2 - Alva-Manchego, Fernando
A2 - Zampieri, Marcos
A2 - North, Kai
A2 - Štajner, Sanja
A2 - Stodden, Regina
PB - Association for Computational Linguistics (ACL Anthology)
CY - Kerrville
Y2 - 15 November 2024
ER -
