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Context is everything, even in commonsense moral reasoning.
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, et al. 2020 · 1901
Earlier work this paper cites.
Manual and automatic evaluation of summaries
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Earlier work this paper cites.
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Earlier work this paper cites.
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Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q Weinberger, and Yoav Artzi. 2019 · 2019
Earlier work this paper cites.
Social chemistry 101: Learning to reason about social and moral norms
Maxwell Forbes, Jena D Hwang, Vered Shwartz, Maarten Sap, and Yejin Choi. 2020 · 2020
Earlier work this paper cites.
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Vaibhav Kumar and Alan W Black. 2020 · 2020
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The logic of universalization guides moral judgment
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Thinking like a skeptic: Defeasible inference in natural language
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Penguins don’t fly: Reasoning about generics through instantiations and exceptions
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Can machines learn morality? the delphi experiment
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Rainier: Reinforced knowledge introspector for commonsense question answering
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