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Large Language Models (LLMs) have demonstrated near-human performance in summarization tasks based on traditional metrics such as ROUGE and BERTScore.
Language Models are Few-Shot Learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel Ziegler, Jeffrey Wu, Clemens Winter, Chris Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020 · 1901
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Bertscore: Evaluating text generation with bert
Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q Weinberger, and Yoav Artzi. 2019 · 1904
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A new measure of rank correlation
MG KENDALL. 1938 · 1938
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The proof and measurement of association between two things
Charles Spearman. 1961 · 1961
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Longformer: The long-document transformer
Iz Beltagy, Matthew E Peters, and Arman Cohan. 2020 · 2004
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Rouge: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
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Textrank: Bringing order into text
Rada Mihalcea and Paul Tarau. 2004 · 2004
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Chapter 12: Significance and measures of association
R Botsch. 2011 · 2011
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Leveraging linguistic structure for open domain information extraction
Gabor Angeli, Melvin Jose Johnson Premkumar, and Christopher D. Manning. 2015 · 2015
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BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
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Knowledge graph completion: A review
Zhe Chen, Yuehan Wang, Bin Zhao, Jing Cheng, Xin Zhao, and Zongtao Duan. 2020 · 2020
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On extractive and abstractive neural document summarization with transformer language models
Jonathan Pilault, Raymond Li, Sandeep Subramanian, and Chris Pal. 2020 · 2020
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Ease: Extractive-abstractive summarization with explanations
Haoran Li, Arash Einolghozati, Srinivasan Iyer, Bhargavi Paranjape, Yashar Mehdad, Sonal Gupta, and Marjan Ghazvininejad. 2021 · 2021
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Recursively summarizing books with human feedback
Jeff Wu, Long Ouyang, Daniel M Ziegler, Nisan Stiennon, Ryan Lowe, Jan Leike, and Paul Christiano. 2021 · 2021
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Bartscore: Evaluating generated text as text generation
Weizhe Yuan, Graham Neubig, and Pengfei Liu. 2021 · 2021
Cited alongside, same era.
Enhanced story comprehension for large language models through dynamic document-based knowledge graphs
Berkeley R Andrus, Yeganeh Nasiri, Shilong Cui, Benjamin Cullen, and Nancy Fulda. 2022 · 2022
Cited alongside, same era.
Longt5: Efficient text-to-text transformer for long sequences
Mandy Guo, Joshua Ainslie, David C Uthus, Santiago Ontanon, Jianmo Ni, Yun-Hsuan Sung, and Yinfei Yang. 2022 · 2022
Cited alongside, same era.
Semantic self-segmentation for abstractive summarization of long documents in low-resource regimes
Gianluca Moro and Luca Ragazzi. 2022 · 2022
Cited alongside, same era.
Summn̂: A multi-stage summarization framework for long input dialogues and documents
Yusen Zhang, Ansong Ni, Ziming Mao, Chen Henry Wu, Chenguang Zhu, Budhaditya Deb, Ahmed Awadallah, Dragomir Radev, and Rui Zhang. 2022 · 2022
Cited alongside, same era.
Booookscore: A systematic exploration of book-length summarization in the era of LLMs
Yapei Chang, Kyle Lo, Tanya Goyal, and Mohit Iyyer. 2024 · 2024
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M3-embedding: multi-linguality, multi-functionality, multi-granularity text embeddings through self-knowledge distillation
Jianlyu Chen, Shitao Xiao, Peitian Zhang, Kun Luo, Defu Lian, and Zheng Liu. 2024 · 2024
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Abhimanyu Dubey, Abhinav Jauhri, Abhinav Pandey, Abhishek Kadian, Ahmad Al-Dahle, Aiesha Letman, Akhil Mathur, Alan Schelten, Amy Yang, Angela Fan, et al. 2024 · 2024
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CHIRON: Rich character representations in long-form narratives
Alexander Gurung and Mirella Lapata. 2024 · 2024
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FABLES: Evaluating faithfulness and content selection in book-length summarization
Yekyung Kim, Yapei Chang, Marzena Karpinska, Aparna Garimella, Varun Manjunatha, Kyle Lo, Tanya Goyal, and Mohit Iyyer. 2024 · 2024
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Can large language models be an alternative to human evaluations?
Cheng-Han Chiang and Hung-yi Lee. 2023 · 2023
Cited alongside, same era.
FActScore: Fine-grained atomic evaluation of factual precision in long form text generation
Sewon Min, Kalpesh Krishna, Xinxi Lyu, Mike Lewis, Wen-tau Yih, Pang Koh, Mohit Iyyer, Luke Zettlemoyer, and Hannaneh Hajishirzi. 2023 · 2023
Cited alongside, same era.
Align-then-abstract representation learning for low-resource summarization
Gianluca Moro and Luca Ragazzi. 2023 · 2023
Cited alongside, same era.
OpenAI. 2023 · 2023
Cited alongside, same era.
Summarization is (almost) dead
Xiao Pu, Mingqi Gao, and Xiaojun Wan. 2023 · 2023
Cited alongside, same era.
Self-consistency improves chain of thought reasoning in language models
Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc V Le, Ed H. Chi, Sharan Narang, Aakanksha Chowdhery, and Denny Zhou. 2023 · 2023
Cited alongside, same era.
LongDocFACTScore: Evaluating the factuality of long document abstractive summarisation
Jennifer A. Bishop, Sophia Ananiadou, and Qianqian Xie. 2024 · 2024
Cited alongside, same era.
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Lost in the middle: How language models use long contexts
Nelson F Liu, Kevin Lin, John Hewitt, Ashwin Paranjape, Michele Bevilacqua, Fabio Petroni, and Percy Liang. 2024 · 2024
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Self-refine: Iterative refinement with self-feedback
Aman Madaan, Niket Tandon, Prakhar Gupta, Skyler Hallinan, Luyu Gao, Sarah Wiegreffe, Uri Alon, Nouha Dziri, Shrimai Prabhumoye, Yiming Yang, et al. 2024 · 2024
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Qwen2.5: A party of foundation models
Qwen Team. 2024 · 2024
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Moviesum: An abstractive summarization dataset for movie screenplays
Rohit Saxena and Frank Keller. 2024a · 2024
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Select and summarize: Scene saliency for movie script summarization
Rohit Saxena and Frank Keller. 2024b · 2024
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Storysumm: Evaluating faithfulness in story summarization
Melanie Subbiah, Faisal Ladhak, Akankshya Mishra, Griffin Adams, Lydia Chilton, and Kathleen Mckeown. 2024 · 2024
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Large language models fall short: Understanding complex relationships in detective narratives
Runcong Zhao, Qinglin Zhu, Hainiu Xu, Jiazheng Li, Yuxiang Zhou, Yulan He, and Lin Gui. 2024 · 2024
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Agent-as-a-judge: Evaluate agents with agents
Mingchen Zhuge, Changsheng Zhao, Dylan Ashley, Wenyi Wang, Dmitrii Khizbullin, Yunyang Xiong, Zechun Liu, Ernie Chang, Raghuraman Krishnamoorthi, Yuandong Tian, et al. 2024 · 2024
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