HeterGraphLongSum: Heterogeneous Graph Neural Network with Passage Aggregation for Extractive Long Document Summarization (2022.coling-1)
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| Challenge: | Existing models for extractive document summarization are based on sequence-to-sequence (Seq2Sequency) but long-form document summaries using graph-based methods are still an open research issue. |
| Approach: | They propose a heterogeneous graph neural network model to improve the performance of extractive document summarization using graph-based methods. |
| Outcome: | The proposed model can achieve state-of-the-art performance without pre-trained language models. |
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