@inproceedings{shi-etal-2024-autodsl,
title = "{A}uto{DSL}: Automated domain-specific language design for structural representation of procedures with constraints",
author = "Shi, Yu-Zhe and
Hou, Haofei and
Bi, Zhangqian and
Meng, Fanxu and
Wei, Xiang and
Ruan, Lecheng and
Wang, Qining",
editor = "Ku, Lun-Wei and
Martins, Andre and
Srikumar, Vivek",
booktitle = "Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
month = aug,
year = "2024",
address = "Bangkok, Thailand",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.luhme-long.659/",
doi = "10.18653/v1/2024.acl-long.659",
pages = "12177--12214",
abstract = "Accurate representation of procedures in restricted scenarios, such as non-standardized scientific experiments, requires precise depiction of constraints. Unfortunately, Domain-specific Language (DSL), as an effective tool to express constraints structurally, often requires case-by-case hand-crafting, necessitating customized, labor-intensive efforts. To overcome this challenge, we introduce the AutoDSL framework to automate DSL-based constraint design across various domains. Utilizing domain specified experimental protocol corpora, AutoDSL optimizes syntactic constraints and abstracts semantic constraints. Quantitative and qualitative analyses of the DSLs designed by AutoDSL across five distinct domains highlight its potential as an auxiliary module for language models, aiming to improve procedural planning and execution."
}
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<abstract>Accurate representation of procedures in restricted scenarios, such as non-standardized scientific experiments, requires precise depiction of constraints. Unfortunately, Domain-specific Language (DSL), as an effective tool to express constraints structurally, often requires case-by-case hand-crafting, necessitating customized, labor-intensive efforts. To overcome this challenge, we introduce the AutoDSL framework to automate DSL-based constraint design across various domains. Utilizing domain specified experimental protocol corpora, AutoDSL optimizes syntactic constraints and abstracts semantic constraints. Quantitative and qualitative analyses of the DSLs designed by AutoDSL across five distinct domains highlight its potential as an auxiliary module for language models, aiming to improve procedural planning and execution.</abstract>
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%0 Conference Proceedings
%T AutoDSL: Automated domain-specific language design for structural representation of procedures with constraints
%A Shi, Yu-Zhe
%A Hou, Haofei
%A Bi, Zhangqian
%A Meng, Fanxu
%A Wei, Xiang
%A Ruan, Lecheng
%A Wang, Qining
%Y Ku, Lun-Wei
%Y Martins, Andre
%Y Srikumar, Vivek
%S Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
%D 2024
%8 August
%I Association for Computational Linguistics
%C Bangkok, Thailand
%F shi-etal-2024-autodsl
%X Accurate representation of procedures in restricted scenarios, such as non-standardized scientific experiments, requires precise depiction of constraints. Unfortunately, Domain-specific Language (DSL), as an effective tool to express constraints structurally, often requires case-by-case hand-crafting, necessitating customized, labor-intensive efforts. To overcome this challenge, we introduce the AutoDSL framework to automate DSL-based constraint design across various domains. Utilizing domain specified experimental protocol corpora, AutoDSL optimizes syntactic constraints and abstracts semantic constraints. Quantitative and qualitative analyses of the DSLs designed by AutoDSL across five distinct domains highlight its potential as an auxiliary module for language models, aiming to improve procedural planning and execution.
%R 10.18653/v1/2024.acl-long.659
%U https://aclanthology.org/2024.luhme-long.659/
%U https://doi.org/10.18653/v1/2024.acl-long.659
%P 12177-12214
Markdown (Informal)
[AutoDSL: Automated domain-specific language design for structural representation of procedures with constraints](https://aclanthology.org/2024.luhme-long.659/) (Shi et al., ACL 2024)
ACL