@inproceedings{zhong-etal-2020-semantic-scaffolds,
title = "Semantic Scaffolds for Pseudocode-to-Code Generation",
author = "Zhong, Ruiqi and
Stern, Mitchell and
Klein, Dan",
editor = "Jurafsky, Dan and
Chai, Joyce and
Schluter, Natalie and
Tetreault, Joel",
booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics",
month = jul,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.acl-main.208",
doi = "10.18653/v1/2020.acl-main.208",
pages = "2283--2295",
abstract = "We propose a method for program generation based on semantic scaffolds, lightweight structures representing the high-level semantic and syntactic composition of a program. By first searching over plausible scaffolds then using these as constraints for a beam search over programs, we achieve better coverage of the search space when compared with existing techniques. We apply our hierarchical search method to the SPoC dataset for pseudocode-to-code generation, in which we are given line-level natural language pseudocode annotations and aim to produce a program satisfying execution-based test cases. By using semantic scaffolds during inference, we achieve a 10{\%} absolute improvement in top-100 accuracy over the previous state-of-the-art. Additionally, we require only 11 candidates to reach the top-3000 performance of the previous best approach when tested against unseen problems, demonstrating a substantial improvement in efficiency.",
}
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%0 Conference Proceedings
%T Semantic Scaffolds for Pseudocode-to-Code Generation
%A Zhong, Ruiqi
%A Stern, Mitchell
%A Klein, Dan
%Y Jurafsky, Dan
%Y Chai, Joyce
%Y Schluter, Natalie
%Y Tetreault, Joel
%S Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
%D 2020
%8 July
%I Association for Computational Linguistics
%C Online
%F zhong-etal-2020-semantic-scaffolds
%X We propose a method for program generation based on semantic scaffolds, lightweight structures representing the high-level semantic and syntactic composition of a program. By first searching over plausible scaffolds then using these as constraints for a beam search over programs, we achieve better coverage of the search space when compared with existing techniques. We apply our hierarchical search method to the SPoC dataset for pseudocode-to-code generation, in which we are given line-level natural language pseudocode annotations and aim to produce a program satisfying execution-based test cases. By using semantic scaffolds during inference, we achieve a 10% absolute improvement in top-100 accuracy over the previous state-of-the-art. Additionally, we require only 11 candidates to reach the top-3000 performance of the previous best approach when tested against unseen problems, demonstrating a substantial improvement in efficiency.
%R 10.18653/v1/2020.acl-main.208
%U https://aclanthology.org/2020.acl-main.208
%U https://doi.org/10.18653/v1/2020.acl-main.208
%P 2283-2295
Markdown (Informal)
[Semantic Scaffolds for Pseudocode-to-Code Generation](https://aclanthology.org/2020.acl-main.208) (Zhong et al., ACL 2020)
ACL
- Ruiqi Zhong, Mitchell Stern, and Dan Klein. 2020. Semantic Scaffolds for Pseudocode-to-Code Generation. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 2283–2295, Online. Association for Computational Linguistics.