Daniel Spokoyny, Ivan Lee, Zhao Jin, Taylor Berg-Kirkpatrick. Masked Measurement Prediction: Learning to Jointly Predict Quantities and Units from Textual Context. In Marine Carpuat, Marie-Catherine de Marneffe, Iván Vladimir Meza Ruíz, editors, Findings of the Association for Computational Linguistics: NAACL 2022, Seattle, WA, United States, July 10-15, 2022. pages 17-29, Association for Computational Linguistics, 2022. [doi]
@inproceedings{SpokoynyLJB22,
title = {Masked Measurement Prediction: Learning to Jointly Predict Quantities and Units from Textual Context},
author = {Daniel Spokoyny and Ivan Lee and Zhao Jin and Taylor Berg-Kirkpatrick},
year = {2022},
url = {https://aclanthology.org/2022.findings-naacl.2},
researchr = {https://researchr.org/publication/SpokoynyLJB22},
cites = {0},
citedby = {0},
pages = {17-29},
booktitle = {Findings of the Association for Computational Linguistics: NAACL 2022, Seattle, WA, United States, July 10-15, 2022},
editor = {Marine Carpuat and Marie-Catherine de Marneffe and Iván Vladimir Meza Ruíz},
publisher = {Association for Computational Linguistics},
isbn = {978-1-955917-76-6},
}