Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Posterior calibration and exploratory analysis for natural language
  processing models   Many models in natural language processing define probabilistic distributions
over linguistic structures. We argue that (1) the quality of a model' s
posterior distribution can and should be directly evaluated, as to whether
probabilities correspond to empirical frequencies, and (2) NLP uncertainty can
be projected not only to pipeline components, but also to exploratory data
analysis, telling a user when to trust and not trust the NLP analysis. We
present a method to analyze calibration, and apply it to compare the
miscalibration of several commonly used models. We also contribute a
coreference sampling algorithm that can create confidence intervals for a
political event extraction task.

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The categories of this paper are: cond-mat
36
The categories of this paper are: cmp-lg
15
The categories of this paper are: nucl-ex
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The categories of this paper are: funct-an
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The categories of this paper are: q-fin
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The categories of this paper are: adap-org
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The categories of this paper are: math-ph
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The categories of this paper are: patt-sol
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The categories of this paper are: acc-phys
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The categories of this paper are: solv-int
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The categories of this paper are: hep-ex
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The categories of this paper are: eess
35
The categories of this paper are: mtrl-th
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The categories of this paper are: chao-dyn
12
The categories of this paper are: nucl-th
37
The categories of this paper are: supr-con