Towards Understanding Large-Scale Discourse Structures in Pre-Trained and Fine-Tuned Language Models (2022.naacl-main)
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| Challenge: | Existing approaches to pre-training/fine-tuning are focusing on the alignment of pre-trained and fine-tuned PLMs with large-scale discourse structures. |
| Approach: | They propose a novel approach to infer discourse information for arbitrarily long documents using supervised, distantly supervised and simple baselines. |
| Outcome: | The proposed approach shows that the captured discourse information is local and general, even across fine-tuning tasks. |
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