Measuring Compositional Generalization: A Comprehensive Method on Realistic Data. Keysers, D., Schärli, N., Scales, N., Buisman, H., Furrer, D., Kashubin, S., Momchev, N., Sinopalnikov, D., Stafiniak, L., Tihon, T., Tsarkov, D., Wang, X., van Zee, M., & Bousquet, O. In International Conference of Learning Representations, 2020.
Measuring Compositional Generalization: A Comprehensive Method on Realistic Data [link]Paper  bibtex   13 downloads  
@inproceedings{Keysers2020,
author = {Keysers, Daniel and Sch\"arli, Nathanael and Scales, Nathan and Buisman, Hylke and Furrer, Daniel and Kashubin, Sergii and Momchev, Nikola and Sinopalnikov, Danila and Stafiniak, Lukasz and Tihon, Tibor and Tsarkov, Dmitry and Wang, Xiao and van Zee, Marc and Bousquet, Olivier},
booktitle = {International Conference of Learning Representations},
file = {:Users/shanest/Documents/Library/Keysers et al/International Conference of Learning Representations/Keysers et al. - 2020 - Measuring Compositional Generalization A Comprehensive Method on Realistic Data.pdf:pdf},
keywords = {method: new data,phenomenon: compositionality},
title = {{Measuring Compositional Generalization: A Comprehensive Method on Realistic Data}},
url = {https://openreview.net/pdf?id=SygcCnNKwr},
year = {2020}
}

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