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Extracting Automata from Recurrent Neural Networks Using Queries and Counterexamples
Gail Weiss · Yoav Goldberg · Eran Yahav

Thu Jul 12 09:15 AM -- 12:00 PM (PDT) @ Hall B #19

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 \lstar 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 Information

Gail Weiss (Technion)
Yoav Goldberg (Bar Ilan University)
Eran Yahav (Technion)

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