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Modern natural language generation systems with Large Language Models (LLMs) exhibit the capability to generate a plausible summary of multiple documents; however, it is uncertain if they truly possess the capability of information consolidation to generate summaries, especially on documents with opinionated information.
Automatic evaluation of summaries using n-gram co-occurrence statistics
Chin-Yew Lin and Eduard H. Hovy. 2003 · 2003
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Comprehensive review of opinion summarization
Hyun Duk Kim, Kavita Ganesan, Parikshit Sondhi, and ChengXiang Zhai. 2011 · 2011
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Metagen: An academic meta-review generation system
Chaitanya Bhatia, Tribikram Pradhan, and Sukomal Pal. 2020 · 2020
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A unified dual-view model for review summarization and sentiment classification with inconsistency loss
Hou Pong Chan, Wang Chen, and Irwin King. 2020 · 2020
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Bertscore: Evaluating text generation with BERT
Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q. Weinberger, and Yoav Artzi. 2020 · 2020
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Reinald Kim Amplayo, Stefanos Angelidis, and Mirella Lapata. 2021 · 2021
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Automatic text summarization: A comprehensive survey
Wafaa S. El-Kassas, Cherif R. Salama, Ahmed A. Rafea, and Hoda K. Mohamed. 2021 · 2021
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Investigating efficiently extending transformers for long input summarization
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Sebastian Gehrmann, Elizabeth Clark, and Thibault Sellam. 2023 · 2023
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Yang Liu, Dan Iter, Yichong Xu, Shuohang Wang, Ruochen Xu, and Chenguang Zhu. 2023 · 2023
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OpenAI. 2023 · 2023
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Summarization is (almost) dead
Xiao Pu, Mingqi Gao, and Xiaojun Wan. 2023 · 2023
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A survey of large language models
Wayne Xin Zhao, Kun Zhou, Junyi Li, Tianyi Tang, Xiaolei Wang, Yupeng Hou, Yingqian Min, Beichen Zhang, Junjie Zhang, Zican Dong, Yifan Du, Chen Yang, Yushuo Chen, Zhipeng Chen, Jinhao Jiang, Ruiyang Ren, Yifan Li, Xinyu Tang, Zikang Liu, Peiyu Liu, Jian-Yun Nie, and Ji-Rong Wen. 2023 · 2023
Later among the works it cites.
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Exploring sentiments in summarization: Sentitextrank, an emotional variant of textrank
Md. Murad Hossain, Luca Anselma, and Alessandro Mazzei. 2023 · 2023
Cited alongside, same era.
Summarizing multiple documents with conversational structure for meta-review generation
Miao Li, Eduard Hovy, and Jey Han Lau. 2023a
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Compressed heterogeneous graph for abstractive multi-document summarization
Miao Li, Jianzhong Qi, and Jey Han Lau. 2023b
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Qi Zeng, Mankeerat Sidhu, Hou Pong Chan, Lu Wang, and Heng Ji. 2024 · 2024
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