Papers with MDS task
A Spectral Method for Unsupervised Multi-Document Summarization (2020.emnlp-main)
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| Challenge: | a spectral-based hypothesis is proposed for the unsupervised task of multi-document summarization. |
| Approach: | They propose a spectral-based hypothesis that a summary candidate's spectral impact is closely linked to its spectre. |
| Outcome: | The proposed method has a competitive result compared to state-of-the-art systems. |
SgSum:Transforming Multi-document Summarization into Sub-graph Selection (2021.emnlp-main)
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| Challenge: | Existing extractive multi-document summarization methods score each sentence individually and extract salient sentences one by one. |
| Approach: | They propose a novel framework for extractive multi-document summarization that selects a sub-graph as the summary instead of selecting salient sentences. |
| Outcome: | The proposed framework improves on existing methods on multi-document datasets and human evaluations show it produces more coherent and informative summaries. |
The patient is more dead than alive: exploring the current state of the multi-document summarisation of the biomedical literature (2022.acl-long)
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| Challenge: | Existing evaluation approaches to multi-document summarization of biomedical literature lack consistency and transparency. |
| Approach: | They propose a systematic approach to human evaluation of biomedical summaries and apply it to analyze the summary generated by two current evaluation models. |
| Outcome: | The proposed evaluation framework is based on two state-of-the-art models and examines the summaries generated by the two models to understand the deficiencies of existing evaluation approaches. |
A Hierarchical Encoding-Decoding Scheme for Abstractive Multi-document Summarization (2023.findings-emnlp)
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| Challenge: | Pre-trained language models have been used for abstractive single-document summarization (SDS) but they may not be suitable for multi-document summary (MDS) |
| Approach: | They propose to enforce hierarchy on both encoder and decoder to facilitate multi-document interactions for MDS. |
| Outcome: | Xiao et al. (2019) outperforms or is competitive with the previous best models. |