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cs.CL2021
Finding needles in a haystack: Sampling Structurally-diverse Training Sets from Synthetic Data for Compositional Generalization
Inbar Oren, Jonathan Herzig, Jonathan Berant
Modern semantic parsers suffer from two principal limitations. First, training requires expensive collection of utterance-program pairs. Second, semantic parsers fail to generalize…
cs.CL2020
Improving Compositional Generalization in Semantic Parsing
Inbar Oren, Jonathan Herzig, Nitish Gupta +2
Generalization of models to out-of-distribution (OOD) data has captured tremendous attention recently. Specifically, compositional generalization, i.e., whether a model generalizes…