@inproceedings{f230ffba9cce4cd6b5201b31acb7e922,
title = "Extracting automata from recurrent neural networks using queries and counterexamples",
abstract = "We present a novel algorithm that uses exact learning and abstraction to extract a deterministic finite automaton describing the state dynamics of a given trained RNN. We do this using Angluin's L∗ algorithm as a learner and the trained RNN as an oracle. Our technique efficiently extracts accurate automata from trained RNNs, even when the state vectors are large and require fine differentiation.",
author = "Gail Weiss and Yoav Goldberg and Eran Yahav",
note = "Publisher Copyright: {\textcopyright} 35th International Conference on Machine Learning, ICML 2018.All Rights Reserved.; 35th International Conference on Machine Learning, ICML 2018 ; Conference date: 10-07-2018 Through 15-07-2018",
year = "2018",
month = jan,
day = "1",
language = "American English",
series = "35th International Conference on Machine Learning, ICML 2018",
pages = "8340--8349",
editor = "Jennifer Dy and Andreas Krause",
booktitle = "35th International Conference on Machine Learning, ICML 2018",
}