Papers with bounded stack
On Efficiently Representing Regular Languages as RNNs (2024.findings-acl)
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| Challenge: | Recent work by Hewitt et al. (2020) provides an interpretation of the empirical success of recurrent neural networks (RNNs) as language models (LMs). |
| Approach: | They generalize their construction and show that RNNs can efficiently represent a larger class of LMs than previously claimed. |
| Outcome: | The results suggest that RNNs can represent a larger class of LMs than previously claimed . |