Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Contextualized moral inference   Developing moral awareness in intelligent systems has shifted from a topic of
philosophical inquiry to a critical and practical issue in artificial
intelligence over the past decades. However, automated inference of everyday
moral situations remains an under-explored problem. We present a text-based
approach that predicts people's intuitive judgment of moral vignettes. Our
methodology builds on recent work in contextualized language models and textual
inference of moral sentiment. We show that a contextualized representation
offers a substantial advantage over alternative representations based on word
embeddings and emotion sentiment in inferring human moral judgment, evaluated
and reflected in three independent datasets from moral psychology. We discuss
the promise and limitations of our approach toward automated textual moral
reasoning.

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The categories of this paper are: math
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The categories of this paper are: astro-ph
20
The categories of this paper are: acc-phys
29
The categories of this paper are: funct-an
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The categories of this paper are: bayes-an
23
The categories of this paper are: solv-int
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The categories of this paper are: chao-dyn
37
The categories of this paper are: supr-con
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The categories of this paper are: quant-ph
30
The categories of this paper are: q-alg
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The categories of this paper are: mtrl-th
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The categories of this paper are: comp-gas
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The categories of this paper are: patt-sol
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The categories of this paper are: q-fin
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The categories of this paper are: nucl-th
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The categories of this paper are: gr-qc