Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Probing the Robustness of Trained Metrics for Conversational Dialogue
  Systems   This paper introduces an adversarial method to stress-test trained metrics to
evaluate conversational dialogue systems. The method leverages Reinforcement
Learning to find response strategies that elicit optimal scores from the
trained metrics. We apply our method to test recently proposed trained metrics.
We find that they all are susceptible to giving high scores to responses
generated by relatively simple and obviously flawed strategies that our method
converges on. For instance, simply copying parts of the conversation context to
form a response yields competitive scores or even outperforms responses written
by humans.

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The categories of this paper are: cond-mat
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The categories of this paper are: nucl-th
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The categories of this paper are: nucl-ex
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The categories of this paper are: stat
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The categories of this paper are: chao-dyn
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The categories of this paper are: dg-ga
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The categories of this paper are: alg-geom
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The categories of this paper are: solv-int
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The categories of this paper are: physics
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The categories of this paper are: q-alg
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The categories of this paper are: nlin
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The categories of this paper are: econ
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The categories of this paper are: bayes-an
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The categories of this paper are: patt-sol
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The categories of this paper are: hep-lat
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The categories of this paper are: hep-th