Multiobjective Simulated Annealing-Based Stopwords Substitution for Rubbish Text Attack

Summary

Researchers propose MOSA-S2, a multiobjective simulated annealing method that generates text rubbish examples by substituting input words with meaningless stopwords. The method uses importance-based composite perturbation and a grammatically constrained variant, and it outperforms prior approaches across six text datasets and seven neural models. The authors report that models often keep the same prediction, sometimes with higher confidence, on nonsensical text.

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