Papers by Guy Hacohen
The Grammar-Learning Trajectories of Neural Language Models (2022.acl-long)
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| Challenge: | In this paper, we show that neural language models with different initialization, architecture, and training data acquire linguistic phenomena in a similar order, despite their different end performance. |
| Approach: | They propose to use mutual inductive bias to study linguistic representations implicit in NLMs. |
| Outcome: | The proposed approach shows that NLMs with different initialization, architecture, and training data acquire linguistic phenomena in a similar order, despite their different end performance. |