Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Faster and Better Grammar-based Text-to-SQL Parsing via Clause-level
  Parallel Decoding and Alignment Loss   Grammar-based parsers have achieved high performance in the cross-domain
text-to-SQL parsing task, but suffer from low decoding efficiency due to the
much larger number of actions for grammar selection than that of tokens in SQL
queries. Meanwhile, how to better align SQL clauses and question segments has
been a key challenge for parsing performance. Therefore, this paper proposes
clause-level parallel decoding and alignment loss to enhance two
high-performance grammar-based parsers, i.e., RATSQL and LGESQL. Experimental
results of two parsers show that our method obtains consistent improvements
both in accuracy and decoding speed.

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The categories of this paper are: chem-ph
3
The categories of this paper are: physics
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The categories of this paper are: q-fin
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The categories of this paper are: alg-geom
9
The categories of this paper are: nlin
25
The categories of this paper are: patt-sol
14
The categories of this paper are: math-ph
8
The categories of this paper are: hep-ex
22
The categories of this paper are: chao-dyn
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The categories of this paper are: adap-org
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The categories of this paper are: atom-ph
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The categories of this paper are: bayes-an
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The categories of this paper are: hep-th
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The categories of this paper are: acc-phys
2
The categories of this paper are: math
16
The categories of this paper are: stat