Overview and Results: CL-SciSumm Shared Task 2019
The CL-SciSumm Shared Task is the first medium-scale shared task on scientific document summarization in the computational linguistics~(CL) domain. In 2019, it comprised three tasks: (1A) identifying relationships between citing documents and the referred document, (1B) classifying the discourse facets, and (2) generating the abstractive summary. The dataset comprised 40 annotated sets of citing and reference papers of the CL-SciSumm 2018 corpus and 1000 more from the SciSummNet dataset. All papers are from the open access research papers in the CL domain. This overview describes the participation and the official results of the CL-SciSumm 2019 Shared Task, organized as a part of the 42nd Annual Conference of the Special Interest Group in Information Retrieval (SIGIR), held in Paris, France in July 2019. We compare the participating systems in terms of two evaluation metrics and discuss the use of ROUGE as an evaluation metric. The annotated dataset used for this shared task and the scripts used for evaluation can be accessed and used by the community at: https://github.com/WING-NUS/scisumm-corpus.
Code (1)
Tasks
Document SummarizationInformation RetrievalRetrievalScientific Document SummarizationSimilar Papers 제목 키워드 기반
The CL-SciSumm Shared Task 2018: Results and Key Insights
This overview describes the official results of the CL-SciSumm Shared Task 2018 -- the first medium-scale shared task on scientific document summarization in the computational linguistics (CL) domain. This year, the data…
Document SummarizationInformation RetrievalRetrievalScientific Document SummarizationOverview of the CL-SciSumm 2016 Shared Task
Overview and Insights from the Shared Tasks at Scholarly Document Processing 2020: CL-SciSumm, LaySumm and LongSumm
We present the results of three Shared Tasks held at the Scholarly Document Processing Workshop at EMNLP2020: CL-SciSumm, LaySumm and LongSumm. We report on each of the tasks, which received 18 submissions in total, with…
Document SummarizationCIST@CL-SciSumm 2020, LongSumm 2020: Automatic Scientific Document Summarization
Our system participates in two shared tasks, CL-SciSumm 2020 and LongSumm 2020. In the CL-SciSumm shared task, based on our previous work, we apply more machine learning methods on position features and content features …
Abstractive Text SummarizationDocument SummarizationExtractive SummarizationPosition+11A-Team / Martin-Luther-Universität Halle-Wittenberg@CLSciSumm 20
This document demonstrates our groups approach to the CL-SciSumm shared task 2020. There are three tasks in CL-SciSumm 2020. In Task 1a, we apply a Siamese neural network to identify the spans of text in the reference pa…