Papers by Petar Milin
CxGBERT: BERT meets Construction Grammar (2020.coling-main)
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| Challenge: | lexico-semantic elements capture a large amount of linguistic information, but they do not capture all information contained in text. |
| Approach: | They propose to use BERT to train a model that uses a deep bidirectional transformer to capture a significant amount of lexico-semantic information. |
| Outcome: | The proposed model captures lexico-semantic information, but it is redundantly encoded in lexical information. |
Abstraction not Memory: BERT and the English Article System (2022.naacl-main)
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| Challenge: | Pre-trained models are the state of the art in linguistics. |
| Approach: | They compare the performance of pre-trained and native English language models on the task of article prediction set up as a three way choice (a/an, the, zero) they argue that BERT captures a high level generalisation of article use akin to human intuition. |
| Outcome: | The proposed model outperforms humans on the linguistically interesting task of article prediction. |