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Simulating Weighted Automata over Sequences and Trees with Transformers
Recent work has shown that these models can compactly simulate the sequential reasoning abilities of deterministic finite automata (DFAs).
Extracting Weighted Automata for Approximate Minimization in Language Modelling
The objective is to obtain a weighted finite automaton (WFA) that fits within a given size constraint and which mimics the behaviour of the original model while minimizing some notion of distance between the black box and the extracted WFA.
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