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Large Language Models (LLMs) have shown promising results in a variety of literary tasks, often using complex memorized details of narration and fictional characters.
The central role of the propensity score in observational studies for causal effects
Paul R. Rosenbaum and Donald B. Rubin. 1983 · 1983
Earlier work this paper cites.
Extracting social networks from literary fiction
David Elson, Nicholas Dames, and Kathleen McKeown. 2010 · 2010
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Extracting training data from large language models
Nicholas Carlini, Florian Tramer, Eric Wallace, Matthew Jagielski, Ariel Herbert-Voss, Katherine Lee, Adam Roberts, Tom Brown, Dawn Song, Ulfar Erlingsson, Alina Oprea, and Colin Raffel. 2021 · 2012
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A sequence labelling approach to quote attribution
Timothy O’Keefe, Silvia Pareti, James R. Curran, Irena Koprinska, and Matthew Honnibal. 2012 · 2012
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Privacy risk in machine learning: Analyzing the connection to overfitting
Samuel Yeom, Irene Giacomelli, Matt Fredrikson, and Somesh Jha. 2018 · 2018
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BERT for coreference resolution: Baselines and analysis
Mandar Joshi, Omer Levy, Luke Zettlemoyer, and Daniel Weld. 2019 · 2019
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Extraction and analysis of fictional character networks: A survey
Vincent Labatut and Xavier Bost. 2019 · 2019
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Measuring information propagation in literary social networks
Matthew Sims and David Bamman. 2020 · 2020
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Deduplicating training data makes language models better
Katherine Lee, Daphne Ippolito, Andrew Nystrom, Chiyuan Zhang, Douglas Eck, Chris Callison-Burch, and Nicholas Carlini. 2022 · 2022
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Data contamination: From memorization to exploitation
Inbal Magar and Roy Schwartz. 2022 · 2022
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Quantifying privacy risks of masked language models using membership inference attacks
Fatemehsadat Mireshghallah, Kartik Goyal, Archit Uniyal, Taylor Berg-Kirkpatrick, and Reza Shokri. 2022 · 2022
Earlier work this paper cites.
Impact of pretraining term frequencies on few-shot numerical reasoning
Yasaman Razeghi, Robert L Logan IV, Matt Gardner, and Sameer Singh. 2022a · 2022
Earlier work this paper cites.
Impact of pretraining term frequencies on few-shot numerical reasoning
Yasaman Razeghi, Robert L Logan IV, Matt Gardner, and Sameer Singh. 2022b · 2022
Cited alongside, same era.
Heroes, villains, and victims, and GPT-3: Automated extraction of character roles without training data
Dominik Stammbach, Maria Antoniak, and Elliott Ash. 2022 · 2022
Cited alongside, same era.
The project dialogism novel corpus: A dataset for quotation attribution in literary texts
Krishnapriya Vishnubhotla, Adam Hammond, and Graeme Hirst. 2022 · 2022
Cited alongside, same era.
Chain of thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, brian ichter, Fei Xia, Ed H. Chi, Quoc V Le, and Denny Zhou. 2022 · 2022
Cited alongside, same era.
Quantifying memorization across neural language models
Nicholas Carlini, Daphne Ippolito, Matthew Jagielski, Katherine Lee, Florian Tramer, and Chiyuan Zhang. 2023 · 2023
Cited alongside, same era.
Retrieval meets long context large language models
Peng Xu, Wei Ping, Xianchao Wu, Lawrence McAfee, Chen Zhu, Zihan Liu, Sandeep Subramanian, Evelina Bakhturina, Mohammad Shoeybi, and Bryan Catanzaro. 2023 · 2023
Later among the works it cites.
Personality understanding of fictional characters during book reading
Mo Yu, Jiangnan Li, Shunyu Yao, Wenjie Pang, Xiaochen Zhou, Zhou Xiao, Fandong Meng, and Jie Zhou. 2023 · 2023
Later among the works it cites.
On classification with large language models in cultural analytics
David Bamman, Kent K. Chang, Li Lucy, and Naitian Zhou. 2024 · 2024
Closest in time.
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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Speak, memory: An archaeology of books known to ChatGPT/GPT-4
Kent Chang, Mackenzie Cramer, Sandeep Soni, and David Bamman. 2023 · 2023
Cited alongside, same era.
Task contamination: Language models may not be few-shot anymore
Changmao Li and Jeffrey Flanigan. 2023 · 2023
Cited alongside, same era.
Grounding characters and places in narrative text
Sandeep Soni, Amanpreet Sihra, Elizabeth Evans, Matthew Wilkens, and David Bamman. 2023 · 2023
Cited alongside, same era.
Sig: Speaker identification in literature via prompt-based generation
Zhenlin Su, Liyan Xu, Jin Xu, Jiangnan Li, and Mingdu Huangfu. 2023 · 2023
Cited alongside, same era.
Using gpt-4 to measure the passage of time in fiction
Ted Underwood. 2023 · 2023
Cited alongside, same era.
Improving automatic quotation attribution in literary novels
Krishnapriya Vishnubhotla, Frank Rudzicz, Graeme Hirst, and Adam Hammond. 2023 · 2023
Cited alongside, same era.
Dialogism in the novel: A computational model of the dialogic nature of narration and quotations
Grace Muzny, Mark Algee-Hewitt, and Dan Jurafsky. 2017a
Cited in the paper.
Story embeddings — narrative-focused representations of fictional stories
Hans Ole Hatzel and Chris Biemann. 2024 · 2024
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Story morals: Surfacing value-driven narrative schemas using large language models
David G Hobson, Haiqi Zhou, Derek Ruths, and Andrew Piper. 2024 · 2024
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Improving quotation attribution with fictional character embeddings
Gaspard Michel, Elena V. Epure, Romain Hennequin, and Christophe Cerisara. 2024 · 2024
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Using large language models for understanding narrative discourse
Andrew Piper and Sunyam Bagga. 2024 · 2024
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Detecting pretraining data from large language models
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Novelqa: A benchmark for long-range novel question answering
Cunxiang Wang, Ruoxi Ning, Boqi Pan, Tonghui Wu, Qipeng Guo, Cheng Deng, Guangsheng Bao, Qian Wang, and Yue Zhang. 2024 · 2024
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NarrativePlay: Interactive narrative understanding
Runcong Zhao, Wenjia Zhang, Jiazheng Li, Lixing Zhu, Yanran Li, Yulan He, and Lin Gui. 2024 · 2024
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