Neural-Symbolic Inference for Robust Autoregressive Graph Parsing via Compositional Uncertainty Quantification
Pre-trained seq2seq models excel at graph semantic parsing with rich annotated data, but
generalize worse to out-of-distribution (OOD) and long-tail examples. In comparison …
generalize worse to out-of-distribution (OOD) and long-tail examples. In comparison …
Cst5: Data augmentation for code-switched semantic parsing
Extending semantic parsers to code-switched input has been a challenging problem,
primarily due to a lack of supervised training data. In this work, we introduce CST5, a new …
primarily due to a lack of supervised training data. In this work, we introduce CST5, a new …