Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Say What I Want: Towards the Dark Side of Neural Dialogue Models   Neural dialogue models have been widely adopted in various chatbot
applications because of their good performance in simulating and generalizing
human conversations. However, there exists a dark side of these models -- due
to the vulnerability of neural networks, a neural dialogue model can be
manipulated by users to say what they want, which brings in concerns about the
security of practical chatbot services. In this work, we investigate whether we
can craft inputs that lead a well-trained black-box neural dialogue model to
generate targeted outputs. We formulate this as a reinforcement learning (RL)
problem and train a Reverse Dialogue Generator which efficiently finds such
inputs for targeted outputs. Experiments conducted on a representative neural
dialogue model show that our proposed model is able to discover such desired
inputs in a considerable portion of cases. Overall, our work reveals this
weakness of neural dialogue models and may prompt further researches of
developing corresponding solutions to avoid it.

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The categories of this paper are: alg-geom
9
The categories of this paper are: nlin
2
The categories of this paper are: math
21
The categories of this paper are: adap-org
5
The categories of this paper are: gr-qc
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The categories of this paper are: funct-an
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The categories of this paper are: ao-sci
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The categories of this paper are: patt-sol
11
The categories of this paper are: hep-lat
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The categories of this paper are: chem-ph
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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: acc-phys
13
The categories of this paper are: quant-ph
35
The categories of this paper are: mtrl-th
6
The categories of this paper are: astro-ph