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Current abstractive summarization models either suffer from a lack of clear interpretability or provide incomplete rationales by only highlighting parts of the source document.
Scoring sentence singletons and pairs for abstractive summarization
Logan Lebanoff, Kaiqiang Song, Franck Dernoncourt, Doo Soon Kim, Seokhwan Kim, Walter Chang, and Fei Liu · 1906
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Text summarization with pretrained encoders
Yang Liu and Mirella Lapata · 1908
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Self-assembling modular networks for interpretable multi-hop reasoning
Yichen Jiang and Mohit Bansal · 1909
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Exploring the limits of transfer learning with a unified text-to-text transformer
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Neural module networks for reasoning over text
Nitish Gupta, Kevin Lin, Dan Roth, Sameer Singh, and Matt Gardner · 1912
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PEGASUS: Pre-training with extracted gap-sentences for abstractive summarization
Jingqing Zhang, Yao Zhao, Mohammad Saleh, and Peter Liu · 1912
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Cognitive psychology and discourse: Recalling and summarizing stories
Walter Kintsch and Teun van Dijk · 1978
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Macrorules for summarizing texts: The development of expertise
Ann L Brown and Jeanne D Day · 1983
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An introduction to the bootstrap
Bradley Efron and Robert J Tibshirani · 1994
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The decomposition of human-written summary sentences
Hongyan Jing and Kathleen R McKeown · 1999
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ROUGE: A package for automatic evaluation of summaries
Chin-Yew Lin · 2004
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Conversational neuro-symbolic commonsense reasoning
Forough Arabshahi, Jennifer Lee, Mikayla Gawarecki, Kathryn Mazaitis, Amos Azaria, and Tom Mitchell · 2006
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Seal: Segment-wise extractive-abstractive long-form text summarization
Yao Zhao, Mohammad Saleh, and Peter J Liu · 2006
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Text modular networks: Learning to decompose tasks in the language of existing models
Tushar Khot, Daniel Khashabi, Kyle Richardson, Peter Clark, and Ashish Sabharwal · 2009
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Artificial Intelligence: a modern approach
Stuart J. Russell and Peter Norvig · 2009
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Learning to fuse sentences with transformers for summarization
Logan Lebanoff, Franck Dernoncourt, Doo Soon Kim, Lidan Wang, Walter Chang, and Fei Liu · 2010
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Braid: Weaving symbolic and neural knowledge into coherent logical explanations
Aditya Kalyanpur, Tom Breloff, David Ferrucci, Adam Lally, and John Jantos · 2011
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ProofWriter: Generating implications, proofs, and abductive statements over natural language
Oyvind Tafjord, Bhavana Dalvi, and Peter Clark · 2012
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Overcoming the lack of parallel data in sentence compression
Katja Filippova and Yasemin Altun · 2013
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Teaching machines to read and comprehend
Karl Moritz Hermann, Tomas Kocisky, Edward Grefenstette, Lasse Espeholt, Will Kay, Mustafa Suleyman, and Phil Blunsom · 2015
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Neural module networks
Jacob Andreas, Marcus Rohrbach, Trevor Darrell, and Dan Klein · 2016
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Towards a rigorous science of interpretable machine learning
Finale Doshi-Velez and Been Kim · 2017
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Faithful to the original: Fact aware neural abstractive summarization
Ziqiang Cao, Furu Wei, Wenjie Li, and Sujian Li · 2018
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Bottom-up abstractive summarization
Sebastian Gehrmann, Yuntian Deng, and Alexander M Rush · 2018
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Explaining answers with entailment trees
Bhavana Dalvi, Peter Jansen, Oyvind Tafjord, Zhengnan Xie, Hannah Smith, Leighanna Pipatanangkura, and Peter Clark · 2021
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A mathematical framework for transformer circuits
N Elhage, N Nanda, C Olsson, T Henighan, N Joseph, B Mann, A Askell, Y Bai, A Chen, T Conerly, et al · 2021
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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
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Show your work: Scratchpads for intermediate computation with language models
Maxwell Nye, Anders Johan Andreassen, Guy Gur-Ari, Henryk Michalewski, Jacob Austin, David Bieber, David Dohan, Aitor Lewkowycz, Maarten Bosma, David Luan, et al · 2021
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multiPRover: Generating multiple proofs for improved interpretability in rule reasoning
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Wan-Ting Hsu, Chieh-Kai Lin, Ming-Ying Lee, Kerui Min, Jing Tang, and Min Sun · 2018
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Explainable neural computation via stack neural module networks
Ronghang Hu, Jacob Andreas, Trevor Darrell, and Kate Saenko · 2018
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Don’t give me the details, just the summary! topic-aware convolutional neural networks for extreme summarization
Shashi Narayan, Shay B Cohen, and Mirella Lapata · 2018
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DiscoFuse: A large-scale dataset for discourse-based sentence fusion
Mor Geva, Eric Malmi, Idan Szpektor, and Jonathan Berant · 2019
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Single document summarization as tree induction
Yang Liu, Ivan Titov, and Mirella Lapata · 2019
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Is attention interpretable?
Sofia Serrano and Noah A Smith · 2019
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Attention is not not explanation
Sarah Wiegreffe and Yuval Pinter · 2019
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QuestEval: Summarization asks for fact-based evaluation
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Ethical and social risks of harm from language models
Laura Weidinger, John Mellor, Maribeth Rauh, Conor Griffin, Jonathan Uesato, Po-Sen Huang, Myra Cheng, Mia Glaese, Borja Balle, Atoosa Kasirzadeh, et al · 2021
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Natural language deduction through search over statement compositions
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