ECONET: Effective Continual Pretraining of Language Models for Event Temporal Reasoning (2021.emnlp-main)
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| Challenge: | Pre-trained language models (PTLMs) have achieved noticeable success on many NLP tasks, but struggle for tasks that require event temporal reasoning. |
| Approach: | They propose a continual pre-training approach that equips PTLMs with targeted knowledge about event temporal relations by focusing on masked-out event and temporal indicators and discriminating sentences from their corrupted counterparts. |
| Outcome: | The proposed framework improves the PTLMs’ fine-tuning performances across five relation extraction and question answering tasks and achieves new or on-par state-of-the-art in most of our downstream tasks. |
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