Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Proving Equivalence Between Complex Expressions Using Graph-to-Sequence
  Neural Models   We target the problem of provably computing the equivalence between two
complex expression trees. To this end, we formalize the problem of equivalence
between two such programs as finding a set of semantics-preserving rewrite
rules from one into the other, such that after the rewrite the two programs are
structurally identical, and therefore trivially equivalent.We then develop a
graph-to-sequence neural network system for program equivalence, trained to
produce such rewrite sequences from a carefully crafted automatic example
generation algorithm. We extensively evaluate our system on a rich multi-type
linear algebra expression language, using arbitrary combinations of 100+
graph-rewriting axioms of equivalence. Our machine learning system guarantees
correctness for all true negatives, and ensures 0 false positive by design. It
outputs via inference a valid proof of equivalence for 93% of the 10,000
equivalent expression pairs isolated for testing, using up to 50-term
expressions. In all cases, the validity of the sequence produced and therefore
the provable assertion of program equivalence is always computable, in
negligible time.

30
The categories of this paper are: q-alg
18
The categories of this paper are: econ
12
The categories of this paper are: nucl-th
6
The categories of this paper are: astro-ph
3
The categories of this paper are: physics
8
The categories of this paper are: hep-ex
32
The categories of this paper are: atom-ph
16
The categories of this paper are: stat
35
The categories of this paper are: mtrl-th
10
The categories of this paper are: q-bio
22
The categories of this paper are: chao-dyn
28
The categories of this paper are: alg-geom
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The categories of this paper are: bayes-an
5
The categories of this paper are: gr-qc
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The categories of this paper are: acc-phys
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The categories of this paper are: ao-sci