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cs.CL2024
Precision, Stability, and Generalization: A Comprehensive Assessment of RNNs learnability capability for Classifying Counter and Dyck Languages
Neisarg Dave, Daniel Kifer, Lee Giles +1
This study investigates the learnability of Recurrent Neural Networks (RNNs) in classifying structured formal languages, focusing on counter and Dyck languages. Traditionally, both…
cs.CL2020
Recognizing Long Grammatical Sequences Using Recurrent Networks Augmented With An External Differentiable Stack
Ankur Mali, Alexander Ororbia, Daniel Kifer +1
Recurrent neural networks (RNNs) are a widely used deep architecture for sequence modeling, generation, and prediction. Despite success in applications such as machine translation…