Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Few-Shot Semantic Parsing for New Predicates   In this work, we investigate the problems of semantic parsing in a few-shot
learning setting. In this setting, we are provided with utterance-logical form
pairs per new predicate. The state-of-the-art neural semantic parsers achieve
less than 25% accuracy on benchmark datasets when k= 1. To tackle this problem,
we proposed to i) apply a designated meta-learning method to train the model;
ii) regularize attention scores with alignment statistics; iii) apply a
smoothing technique in pre-training. As a result, our method consistently
outperforms all the baselines in both one and two-shot settings.

18
The categories of this paper are: econ
32
The categories of this paper are: atom-ph
25
The categories of this paper are: patt-sol
23
The categories of this paper are: solv-int
33
The categories of this paper are: plasm-ph
12
The categories of this paper are: nucl-th
19
The categories of this paper are: eess
34
The categories of this paper are: chem-ph
7
The categories of this paper are: hep-th
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The categories of this paper are: astro-ph
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The categories of this paper are: hep-lat
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The categories of this paper are: bayes-an
10
The categories of this paper are: q-bio
31
The categories of this paper are: ao-sci
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The categories of this paper are: nlin
5
The categories of this paper are: gr-qc