Semantic Training Signals Promote Hierarchical Syntactic Generalization in Transformers (2024.emnlp-main)
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| Challenge: | Neural networks without hierarchical biases struggle to learn linguistic rules that come naturally to humans . et al., 2018: Transformers trained on form and meaning favor hierarchically generalization more than those trained on forms alone. |
| Approach: | They examine whether neural networks without hierarchical biases can generalize more like humans . they find that Transformers trained on form and meaning favor hierarchic generalization . |
| Outcome: | The proposed neural networks perform better on syntactic evaluations when trained on form and meaning compared to those trained on forms alone. |
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