Papers by Martin Tappler
On the Relationship Between RNN Hidden-State Vectors and Semantic Structures (2024.findings-acl)
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| Challenge: | Using hidden-state vectors of recurrent neural networks (RNNs) we examine the assumption that hidden- state vectors tend to form clusters of semantically similar vectors, which we dub the clustering hypothesis. |
| Approach: | They propose to use recurrent neural networks (RNNs) that model processes with internal states to test their hypothesis. |
| Outcome: | The proposed model is based on a set of RNNs that were trained to recognize regular languages and a context-free language. |