Papers with neural nets
Are we there yet? Encoder-decoder neural networks as cognitive models of English past tense inflection (P19-1)
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| Challenge: | linguistics and cognitive science have long debated the cognitive mechanisms needed to account for the English past tense. |
| Approach: | They propose to use an encoder-decoder model to account for the english past tense . they also show that ED models demonstrate humanlike performance in a nonce-word task . |
| Outcome: | The proposed model is unstable across simulations and does not fit to human data . other neural models might do better, but there is insufficient evidence to claim them . |
CTL++: Evaluating Generalization on Never-Seen Compositional Patterns of Known Functions, and Compatibility of Neural Representations (2022.emnlp-main)
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| Challenge: | Existing neural nets fail to generalize systematically due to superficial differences in training data. |
| Approach: | They propose a new diagnostic dataset based on compositions of unary symbolic functions that tests systematicity of NNs. |
| Outcome: | The proposed dataset shows that recent CTL-solving Transformer variants fail on CTL++. |