@inproceedings{bonn-etal-2024-meaning,
title = "Meaning Representations for Natural Languages: Design, Models and Applications",
author = "Bonn, Julia and
Flanigan, Jeffrey and
Haji{\v{c}}, Jan and
Jindal, Ishan and
Li, Yunyao and
Xue, Nianwen",
editor = "Klinger, Roman and
Okazaki, Naozaki and
Calzolari, Nicoletta and
Kan, Min-Yen",
booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024): Tutorial Summaries",
month = may,
year = "2024",
address = "Torino, Italia",
publisher = "ELRA and ICCL",
url = "https://aclanthology.org/2024.lrec-tutorials.3",
pages = "13--18",
abstract = "This tutorial reviews the design of common meaning representations, SoTA models for predicting meaning representations, and the applications of meaning representations in a wide range of downstream NLP tasks and real-world applications. Reporting by a diverse team of NLP researchers from academia and industry with extensive experience in designing, building and using meaning representations, our tutorial has three components: (1) an introduction to common meaning representations, including basic concepts and design challenges; (2) a review of SoTA methods on building models for meaning representations; and (3) an overview of applications of meaning representations in downstream NLP tasks and real-world applications. We propose a cutting-edge, full-day tutorial for all stakeholders in the AI community, including NLP researchers, domain-specific practitioners, and students",
}
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%0 Conference Proceedings
%T Meaning Representations for Natural Languages: Design, Models and Applications
%A Bonn, Julia
%A Flanigan, Jeffrey
%A Hajič, Jan
%A Jindal, Ishan
%A Li, Yunyao
%A Xue, Nianwen
%Y Klinger, Roman
%Y Okazaki, Naozaki
%Y Calzolari, Nicoletta
%Y Kan, Min-Yen
%S Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024): Tutorial Summaries
%D 2024
%8 May
%I ELRA and ICCL
%C Torino, Italia
%F bonn-etal-2024-meaning
%X This tutorial reviews the design of common meaning representations, SoTA models for predicting meaning representations, and the applications of meaning representations in a wide range of downstream NLP tasks and real-world applications. Reporting by a diverse team of NLP researchers from academia and industry with extensive experience in designing, building and using meaning representations, our tutorial has three components: (1) an introduction to common meaning representations, including basic concepts and design challenges; (2) a review of SoTA methods on building models for meaning representations; and (3) an overview of applications of meaning representations in downstream NLP tasks and real-world applications. We propose a cutting-edge, full-day tutorial for all stakeholders in the AI community, including NLP researchers, domain-specific practitioners, and students
%U https://aclanthology.org/2024.lrec-tutorials.3
%P 13-18
Markdown (Informal)
[Meaning Representations for Natural Languages: Design, Models and Applications](https://aclanthology.org/2024.lrec-tutorials.3) (Bonn et al., LREC 2024)
ACL
- Julia Bonn, Jeffrey Flanigan, Jan Hajič, Ishan Jindal, Yunyao Li, and Nianwen Xue. 2024. Meaning Representations for Natural Languages: Design, Models and Applications. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024): Tutorial Summaries, pages 13–18, Torino, Italia. ELRA and ICCL.