@inproceedings{he-etal-2023-hermes,
title = "{H}erm{E}s: Interactive Spreadsheet Formula Prediction via Hierarchical Formulet Expansion",
author = "He, Wanrong and
Dong, Haoyu and
Gao, Yihuai and
Fan, Zhichao and
Guo, Xingzhuo and
Hou, Zhitao and
Lv, Xiao and
Jia, Ran and
Han, Shi and
Zhang, Dongmei",
editor = "Rogers, Anna and
Boyd-Graber, Jordan and
Okazaki, Naoaki",
booktitle = "Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.acl-long.465",
doi = "10.18653/v1/2023.acl-long.465",
pages = "8356--8372",
abstract = "We propose HermEs, the first approach for spreadsheet formula prediction via HiEraRchical forMulet ExpanSion, where hierarchical expansion means generating formulas following the underlying parse tree structure, and Formulet refers to commonly-used multi-level patterns mined from real formula parse trees. HermEs improves the formula prediction accuracy by (1) guaranteeing correct grammar by hierarchical generation rather than left-to-right generation and (2) significantly streamlining the token-level decoding with high-level Formulet. Notably, instead of generating formulas in a pre-defined fixed order, we propose a novel sampling strategy to systematically exploit a variety of hierarchical and multi-level expansion orders and provided solid mathematical proof, with the aim of meeting diverse human needs of the formula writing order in real applications. We further develop an interactive formula completion interface based on HermEs, which shows a new user experience in \url{https://github.com/formulet/HERMES}.",
}
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<abstract>We propose HermEs, the first approach for spreadsheet formula prediction via HiEraRchical forMulet ExpanSion, where hierarchical expansion means generating formulas following the underlying parse tree structure, and Formulet refers to commonly-used multi-level patterns mined from real formula parse trees. HermEs improves the formula prediction accuracy by (1) guaranteeing correct grammar by hierarchical generation rather than left-to-right generation and (2) significantly streamlining the token-level decoding with high-level Formulet. Notably, instead of generating formulas in a pre-defined fixed order, we propose a novel sampling strategy to systematically exploit a variety of hierarchical and multi-level expansion orders and provided solid mathematical proof, with the aim of meeting diverse human needs of the formula writing order in real applications. We further develop an interactive formula completion interface based on HermEs, which shows a new user experience in https://github.com/formulet/HERMES.</abstract>
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%0 Conference Proceedings
%T HermEs: Interactive Spreadsheet Formula Prediction via Hierarchical Formulet Expansion
%A He, Wanrong
%A Dong, Haoyu
%A Gao, Yihuai
%A Fan, Zhichao
%A Guo, Xingzhuo
%A Hou, Zhitao
%A Lv, Xiao
%A Jia, Ran
%A Han, Shi
%A Zhang, Dongmei
%Y Rogers, Anna
%Y Boyd-Graber, Jordan
%Y Okazaki, Naoaki
%S Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
%D 2023
%8 July
%I Association for Computational Linguistics
%C Toronto, Canada
%F he-etal-2023-hermes
%X We propose HermEs, the first approach for spreadsheet formula prediction via HiEraRchical forMulet ExpanSion, where hierarchical expansion means generating formulas following the underlying parse tree structure, and Formulet refers to commonly-used multi-level patterns mined from real formula parse trees. HermEs improves the formula prediction accuracy by (1) guaranteeing correct grammar by hierarchical generation rather than left-to-right generation and (2) significantly streamlining the token-level decoding with high-level Formulet. Notably, instead of generating formulas in a pre-defined fixed order, we propose a novel sampling strategy to systematically exploit a variety of hierarchical and multi-level expansion orders and provided solid mathematical proof, with the aim of meeting diverse human needs of the formula writing order in real applications. We further develop an interactive formula completion interface based on HermEs, which shows a new user experience in https://github.com/formulet/HERMES.
%R 10.18653/v1/2023.acl-long.465
%U https://aclanthology.org/2023.acl-long.465
%U https://doi.org/10.18653/v1/2023.acl-long.465
%P 8356-8372
Markdown (Informal)
[HermEs: Interactive Spreadsheet Formula Prediction via Hierarchical Formulet Expansion](https://aclanthology.org/2023.acl-long.465) (He et al., ACL 2023)
ACL
- Wanrong He, Haoyu Dong, Yihuai Gao, Zhichao Fan, Xingzhuo Guo, Zhitao Hou, Xiao Lv, Ran Jia, Shi Han, and Dongmei Zhang. 2023. HermEs: Interactive Spreadsheet Formula Prediction via Hierarchical Formulet Expansion. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 8356–8372, Toronto, Canada. Association for Computational Linguistics.