TESA: A Task in Entity Semantic Aggregation for Abstractive Summarization (2020.emnlp-main)
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| Challenge: | Abstractive summarization systems focus on paraphrasing and simplifying the source content, to the exclusion of such semantic abstraction capabilities. |
| Approach: | They propose a dataset and task to fine tune an abstractive summarization model to generate aggregations of 5.3K entities from a crowd-sourced dataset. |
| Outcome: | The proposed task and dataset show that the proposed model can generate aggregations at a semantic level, but that it is too complex to use. |
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| Challenge: | a simple but flexible mechanism is used to ground the generation of abstractive summaries. |
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| Challenge: | Summarization is the task of shortening a text while preserving the most important information it contains. |
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