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While numerous architectures for long-range language models (LRLMs) have recently been proposed, a meaningful evaluation of their discourse-level language understanding capabilities has not yet followed.
The Chapter in Fiction: Theories of Narrative Division
Philip Stevick. 1970 · 1970
Earlier work this paper cites.
Towards a grammar of narrative sequence: The model of the french lieutenant’s woman
KR Ireland. 1986 · 1986
Earlier work this paper cites.
Maintaining global coherence during reading
Jerome Myers, Edward O’Brien, Jason Albrecht, and Robert Mason. 1994 · 1994
Earlier work this paper cites.
Role of context in accessing distant information during reading
Jason E. Albrecht and Jerome L. Myers. 1995 · 1995
Earlier work this paper cites.
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Tom B Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al. 2020 · 2005
Earlier work this paper cites.
Gmat: Global memory augmentation for transformers
Ankit Gupta and Jonathan Berant. 2020 · 2006
Earlier work this paper cites.
Jason Weston, Sumit Chopra, and Antoine Bordes. 2015 · 2015
Earlier work this paper cites.
Self-attention with relative position representations
Peter Shaw, Jakob Uszkoreit, and Ashish Vaswani. 2018 · 2018
Earlier work this paper cites.
Representation learning with contrastive predictive coding
Aäron van den Oord, Yazhe Li, and Oriol Vinyals. 2018 · 2018
Earlier work this paper cites.
SWAG: A large-scale adversarial dataset for grounded commonsense inference
Rowan Zellers, Yonatan Bisk, Roy Schwartz, and Yejin Choi. 2018 · 2018
Earlier work this paper cites.
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Rewon Child, Scott Gray, Alec Radford, and Ilya Sutskever. 2019 · 2019
Earlier work this paper cites.
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Zihang Dai, Zhilin Yang, Yiming Yang, Jaime Carbonell, Quoc Le, and Ruslan Salakhutdinov. 2019 · 2019
Earlier work this paper cites.
Eli5: Long form question answering
Angela Fan, Yacine Jernite, Ethan Perez, David Grangier, Jason Weston, and Michael Auli. 2019 · 2019
Earlier work this paper cites.
Roberta: A robustly optimized bert pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 2019
Earlier work this paper cites.
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Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 2019 · 2019
Cited alongside, same era.
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Joshua Ainslie, Santiago Ontanon, Chris Alberti, Vaclav Cvicek, Zachary Fisher, Philip Pham, Anirudh Ravula, Sumit Sanghai, Qifan Wang, and Li Yang. 2020 · 2020
Cited alongside, same era.
Longformer: The long-document transformer
Iz Beltagy, Matthew E. Peters, and Arman Cohan. 2020 · 2020
Cited alongside, same era.
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Cited alongside, same era.
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Angelos Katharopoulos, Apoorv Vyas, Nikolaos Pappas, and Francois Fleuret. 2020 · 2020
Efficient attentions for long document summarization
Luyang Huang, Shuyang Cao, Nikolaus Parulian, Heng Ji, and Lu Wang. 2021 · 2021
Later among the works it cites.
Booksum: A collection of datasets for long-form narrative summarization
Wojciech Kryściński, Nazneen Rajani, Divyansh Agarwal, Caiming Xiong, and Dragomir Radev. 2021 · 2021
Later among the works it cites.
Quality: Question answering with long input texts, yes!
Richard Yuanzhe Pang, Alicia Parrish, Nitish Joshi, Nikita Nangia, Jason Phang, Angelica Chen, Vishakh Padmakumar, Johnny Ma, Jana Thompson, He He, and Samuel R. Bowman. 2021 · 2021
Later among the works it cites.
Shortformer: Better language modeling using shorter inputs
Ofir Press, Noah A. Smith, and Mike Lewis. 2021 · 2021
Later among the works it cites.
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Aurko Roy, Mohammad Saffar, Ashish Vaswani, and David Grangier. 2021 · 2021
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Cited alongside, same era.
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Cited alongside, same era.
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Cited alongside, same era.
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Cited alongside, same era.
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