SETSum: Summarization and Visualization of Student Evaluations of Teaching (2022.naacl-demo)
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| Challenge: | Student Evaluations of Teaching (SETs) are used in colleges and universities to assess student perceptions about their courses. |
| Approach: | They propose a system that leverages sentiment analysis, aspect extraction, summarization and visualization techniques to provide organized illustrations of SET findings to instructors and other reviewers. |
| Outcome: | The proposed system can be used by 10 professors from diverse departments to analyze SET results. |
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| Challenge: | Existing research has focused on standard summarization benchmarks within domains like news, scientific articles, and opinions. |
| Approach: | They propose a summarization dataset specifically designed for summarizing students’ reflective writing. |
| Outcome: | The proposed summarization dataset can be used in opinion summarizing scenarios and in educational domains. |
BOOKSUM: A Collection of Datasets for Long-form Narrative Summarization (2022.findings-emnlp)
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| Challenge: | Existing text summarization datasets include short-form source documents that lack long-range causal and temporal dependencies and contain strong layout and stylistic biases. |
| Approach: | They propose a dataset for long-form narrative summarization that uses human written summaries on three levels of difficulty. |
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WikiSum: Coherent Summarization Dataset for Efficient Human-Evaluation (2021.acl-short)
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| Challenge: | Existing summarization datasets are limited in their ability to evaluate output . a human evaluation is necessary to understand and improve summarizing systems . |
| Approach: | They propose a dataset based on how-to articles and coherent paragraph summaries written in plain language. |
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ACLSum: A New Dataset for Aspect-based Summarization of Scientific Publications (2024.naacl-long)
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| Challenge: | Existing statistical phrasal or hierarchical machine translation systems relies on a large set of translation rules which results in engineering challenges. |
| Approach: | They propose to use factorized grammar from the field of linguistics as more general translation rules from XTAG English Grammar to generate a manually crafted summarization dataset. |
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Summary Explorer: Visualizing the State of the Art in Text Summarization (2021.emnlp-demo)
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| Challenge: | Automatic text summarization is the task of generating a summary of a long text by condensing it to its most important parts. |
| Approach: | They propose a tool to visually explore document summarization systems based on three well-known summary quality criteria . |
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ForumSum: A Multi-Speaker Conversation Summarization Dataset (2021.findings-emnlp)
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| Challenge: | Abstractive summarization quality has been improved but there is a lack of data for conversation summarizing applications. |
| Approach: | They propose to build a conversation summarization dataset with human written summaries from internet forums. |
| Outcome: | The proposed dataset can be easily expanded to improve conversation summarization applications. |
From Information to Insight: Leveraging LLMs for Open Aspect-Based Educational Summarization (2025.acl-long)
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| Challenge: | a novel dataset summarizes student reflections on STEM lectures . ReflectASP eases the exploration of open-aspect-based summarization (OABS) despite the limitations of current datasets, it is still under-explored. |
| Approach: | They propose a dataset that summarizes student reflections on STEM lectures . they propose two refinement methods to improve summaries . |
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CaseSumm: A Large-Scale Dataset for Long-Context Summarization from U.S. Supreme Court Opinions (2025.findings-naacl)
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| Challenge: | CaseSumm is a dataset for long-context summarization in the legal domain . human groundtruth summaries are often not available for legal summarizing . |
| Approach: | They propose a dataset for long-context summarization that includes SCOTUS opinions and their official summaries. |
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BillSum: A Corpus for Automatic Summarization of US Legislation (D19-54)
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| Challenge: | In the US Congress, over 10,000 bills are introduced each year, with state legislatures introducing tens of thousands of bills. |
| Approach: | They introduce the first dataset for summarizing US Congressional and California state bills . they demonstrate that models built on Congressional bills can be used to summarize California billa . |
| Outcome: | The proposed summarization methods can be applied to states without human-written summaries. |
Automatic Pyramid Evaluation Exploiting EDU-based Extractive Reference Summaries (D18-1)
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| Challenge: | Existing methods for evaluating content are not accurate because they only confirm if the summary contains small textual fragments. |
| Approach: | They propose to transform human-made reference summaries into extractive reference sums and weight them using elementary discourse units. |
| Outcome: | The proposed method strongly correlates with manual evaluations on DUC and TAC data sets. |