Papers by Marion Di Marco
Extracting Linguistic Information from Large Language Models: Syntactic Relations and Derivational Knowledge (2025.emnlp-main)
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| Challenge: | Using large language models, we study their morphosyntactic competence and generalization capabilities. |
| Approach: | They propose to use morphosyntactic tasks to study their linguistic knowledge and generalization capabilities to extract different types of morphological structure for typologically diverse languages. |
| Outcome: | The proposed models outperform GPT-4o and LLaMA 3.3-70B in all diagnostic tasks, but show little evidence of abstract morphological rule learning. |