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Found 4 papers, 2 papers with code
Improving Compositional Generalization with Latent Structure and Data Augmentation
Generic unstructured neural networks have been shown to struggle on out-of-distribution compositional generalization.
Structured Context and High-Coverage Grammar for Conversational Question Answering over Knowledge Graphs
On CSQA, our approach increases the coverage from $80\%$ to $96. 2\%$, and the LF execution accuracy from $70. 6\%$ to $75. 6\%$, with respect to previous state-of-the-art results.
TAPAS: Weakly Supervised Table Parsing via Pre-training
In this paper, we present TAPAS, an approach to question answering over tables without generating logical forms.
Ranked #1 on
Semantic Parsing
on SQA
(Accuracy metric)
Stiffness: A New Perspective on Generalization in Neural Networks
In particular, we study how stiffness depends on 1) class membership, 2) distance between data points in the input space, 3) training iteration, and 4) learning rate.
