Papers with ROUGE metrics
Ant Colony System for Multi-Document Summarization (C18-1)
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| Challenge: | Existing methods for summarizing documents are greedy and greedy, but they rarely produce the best summaries. |
| Approach: | They propose an extractive multi-document summarization approach based on an ant colony system to optimize information coverage of summary sentences. |
| Outcome: | The proposed system achieves the best scores on both English and Arabic versions of the corpus of the Text Analysis Conference 2011 MultiLing Pilot . |
Attend to Medical Ontologies: Content Selection for Clinical Abstractive Summarization (2020.acl-main)
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| Challenge: | Existing studies have reported that clinicians read the IMPRESSION as they have less time to review findings. |
| Approach: | They propose to augment salient ontological terms into the abstractive summarizer by augmenting salient ontologies into the semantic summariser. |
| Outcome: | The proposed model significantly improves state-of-the-art results in terms of ROUGE metrics on two publicly available clinical data sets. |
Improving Abstractive Document Summarization with Salient Information Modeling (P19-1)
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| Challenge: | Abstractive document summarization is a task of natural language generation which generates fluent summaries with salient information automatically. |
| Approach: | They propose to incorporate a Gaussian focal bias on attention scores into an encoder to enhance the perception of local context and to distinguish salient information precisely. |
| Outcome: | The proposed framework outperforms state-of-the-art models on the CNN/Daily Mail benchmark and is based on a focus-attention mechanism and two new extensions. |
Reading Like HER: Human Reading Inspired Extractive Summarization (D19-1)
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| Challenge: | Existing methods for extracting text summarization are abstractive and extractive. |
| Approach: | They propose a novel approach for extractive summarization by simulating two stages . they adopt a convolutional neural network to encode gist of paragraphs for rough reading . |
| Outcome: | The proposed method significantly outperforms the state-of-the-art extractive methods on CNN and DailyMail datasets. |
JPG - Jointly Learn to Align: Automated Disease Prediction and Radiology Report Generation (2022.coling-1)
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| Challenge: | Existing methods rarely consider cross-modal alignment between textual and visual features and ignore disease tags as auxiliary for report generation. |
| Approach: | They propose a "Jointly learning framework for automated disease Prediction and radiology report Generation" the framework integrates cross-modal alignment between textual and visual features and disease tags to improve the quality of reports. |
| Outcome: | The proposed framework improves the quality of radiology reports by combining the main task and auxiliary tasks. |
Unsupervised Opinion Summarisation in the Wasserstein Space (2022.emnlp-main)
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| Challenge: | Recent work on opinion summarisation of social media posts has focused on reviews . however, it is important to capture user opinions in online discussions over specific topics . |
| Approach: | They propose an unsupervised opinion summarisation model which uses the Wasserstein distance to generate a single summary from a group of documents. |
| Outcome: | The proposed model outperforms the state-of-the-art on ROUGE metrics and produces the best summaries with respect to meaning preservation according to human evaluations. |