Learning Trajectories of Figurative Language for Pre-Trained Language Models (2025.findings-emnlp)
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| Challenge: | Figures of speech and figures of language are used in everyday communication . however, this imaginative use of words requires a solid understanding of semantics and real-world knowledge. |
| Approach: | They exploit probing tasks to analyse how NLMs recognise figurative language . they find out which layers have a better comprehension of figurativ language based on pre-training data. |
| Outcome: | The proposed model can recognise hyperboles, metaphors, oxymorons and pleonasms . data show which layers have a better comprehension of figurative language . |
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