Long document summarization, a challenging summarization scenario, is the focus of the recently proposed LongSumm shared task. One of the limitations of this shared task has been its use of a single family of metrics for evaluation (the ROUGE metrics). In contrast, other fields, like text generation, employ multiple metrics. We replicated the LongSumm evaluation using multiple test set samples (vs. the single test set of the official shared task) and investigated how different metrics might complement each other in this evaluation framework. We show that under this more rigorous evaluation, (1) some of the key learnings from Longsumm 2020 and 2021 still hold, but the relative ranking of systems changes, and (2) the use of additional metrics reveals additional high-quality summaries missed by ROUGE, and (3) we show that SPICE is a candidate metric for summarization evaluation for LongSumm.

Investigating Metric Diversity for Evaluating Long Document Summarisation

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**Workshop overview:** As the body of scholarly literature grows, automated methods in NLP, text mining, information retrieval, document understanding etc. are needed to address issues of information overload, disinformation, reproducibility, and more. Though progress has been made, there are significant unique challenges to processing scholarly text that require dedicated attention. The goal of this workshop is to provide a venue for addressing these challenges, as well as a platform for tasks and resources supporting the processing of scientific documents. Our long-term objective is to establish scholarly and scientific texts as an essential domain for NLP research, to supplement current efforts on web text and news articles.

This workshop builds on the success of prior workshops: the SDP workshop held at NAACL in 2021 and EMNLP in 2020, and the SciNLP workshop held at AKBC 2020 and AKBC 2021. Both workshops received numerous submissions and were well attended, demonstrating that interest in this area seems to be growing rapidly. In addition to having broad appeal within the NLP community, we expect that the SDP workshop will attract researchers from other relevant fields including meta-science, scientometrics, data mining, information retrieval, and digital libraries, bringing together these disparate communities within the ACL. [**Read more.**](https://sdproc.org/2022/) Our detailed schedule can be viewed [**here.**](https://sdproc.org/2022/program.html)

W8 Third Workshop on Scholarly Document Processing (SDP 2022)

workshop paper

[![](https://assets.underline.io/uploads/markdown_image/1/image/81a3c0317d24f663b49b996875024d45.png)](https://aclanthology.org/volumes/2022.coling-1/)



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**COLING**, the International Conference on Computational Linguistics, is one of the premier conferences for the natural language processing and computational linguistics.

First established in 1965, the biennial COLING conference is held in diverse parts of the globe and attracts participants from both top-ranked research centers and emerging countries. Today, the most important developments in our field are taking place not only in universities and academic research institutes but also in industrial research departments including tech-startups. COLING provides opportunities for all these communities to showcase their exciting discovery.

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COLING 2022

COLING, the International Conference on Computational Linguistics, is one of the premier conferences for the natural language processing and computational linguistics.

Cai Yang

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Investigating Metric Diversity for Evaluating Long Document Summarisation

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