Papers with natural language variation

2 papers
Compositional Generalization and Natural Language Variation: Can a Semantic Parsing Approach Handle Both? (2021.acl-long)

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Challenge: Existing approaches to semantic parsing only evaluated on synthetic datasets that are not representative of natural language variation.
Approach: They propose a semantic parsing approach that handles both natural language variation and compositional generalization.
Outcome: The proposed model outperforms existing models across compositional generalization challenges on non-synthetic datasets while being competitive with the state-of-the-art on standard evaluations.
Improving Compositional Generalization with Latent Structure and Data Augmentation (2022.naacl-main)

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Challenge: Generic unstructured neural networks struggle on out-of-distribution compositional generalization.
Approach: They propose a method to recombinate examples from a model called Compositional Structure Learner and add them to a pre-trained sequence-to-sequence model.
Outcome: The proposed model is even stronger than a T5-CSL ensemble on two real world compositional generalization tasks.

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