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On the Linguistic Capacity of Real-Time Counter Automata
[article]
2021
arXiv
pre-print
Counter machines have achieved a newfound relevance to the field of natural language processing (NLP): recent work suggests some strong-performing recurrent neural networks utilize their memory as counters. Thus, one potential way to understand the success of these networks is to revisit the theory of counter computation. Therefore, we study the abilities of real-time counter machines as formal grammars, focusing on formal properties that are relevant for NLP models. We first show that several
arXiv:2004.06866v2
fatcat:dj6luyahcvdy5ga2txeugmoy5q