Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Contextualized Perturbation for Textual Adversarial Attack   Adversarial examples expose the vulnerabilities of natural language
processing (NLP) models, and can be used to evaluate and improve their
robustness. Existing techniques of generating such examples are typically
driven by local heuristic rules that are agnostic to the context, often
resulting in unnatural and ungrammatical outputs. This paper presents CLARE, a
ContextuaLized AdversaRial Example generation model that produces fluent and
grammatical outputs through a mask-then-infill procedure. CLARE builds on a
pre-trained masked language model and modifies the inputs in a context-aware
manner. We propose three contextualized perturbations, Replace, Insert and
Merge, allowing for generating outputs of varied lengths. With a richer range
of available strategies, CLARE is able to attack a victim model more
efficiently with fewer edits. Extensive experiments and human evaluation
demonstrate that CLARE outperforms the baselines in terms of attack success
rate, textual similarity, fluency and grammaticality.

24
The categories of this paper are: dg-ga
29
The categories of this paper are: funct-an
14
The categories of this paper are: math-ph
0
The categories of this paper are: hep-ph
32
The categories of this paper are: atom-ph
15
The categories of this paper are: nucl-ex
8
The categories of this paper are: hep-ex
35
The categories of this paper are: mtrl-th
25
The categories of this paper are: patt-sol
10
The categories of this paper are: q-bio
30
The categories of this paper are: q-alg
13
The categories of this paper are: quant-ph
36
The categories of this paper are: cmp-lg
37
The categories of this paper are: supr-con
22
The categories of this paper are: chao-dyn
31
The categories of this paper are: ao-sci