Papers by Harish Karnick
Unsupervised Semantic Abstractive Summarization (P18-3)
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| Challenge: | Existing methods for abstractive summarization are limited in the sense that they can never generate human level summaries for large and complicated documents. |
| Approach: | They propose a pipeline for automatic abstractive summary generation using co-reference resolution and Meta Nodes. |
| Outcome: | The proposed pipeline outperforms the state-of-the-art method by 1.7% in node prediction. |
SumPubMed: Summarization Dataset of PubMed Scientific Articles (2021.acl-srw)
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| Challenge: | Existing summarization models that can extract the top few lines of news articles fail to summarize long documents. |
| Approach: | They constructed a scientific summarization dataset from MEDLINE articles from the PubMed archive to address this problem. |
| Outcome: | The proposed model outperforms existing models on news article summarization datasets and shows that it is more efficient to extract the top few lines. |