AdvGLUE
Adversarial GLUE
홈페이지 · 논문 36편
Adversarial GLUE (AdvGLUE) is a new multi-task benchmark to quantitatively and thoroughly explore and evaluate the vulnerabilities of modern large-scale language models under various types of adversarial attacks. In particular, we systematically apply 14 textual adversarial attack methods to [GLUE](/dataset/glue) tasks to construct AdvGLUE, which is further validated by humans for reliable annotations. Description from: Adversarial GLUE: A Multi-Task Benchmark for Robustness Evaluation of Language Models
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