PFEemp2024 commited on
Commit
2278636
1 Parent(s): 1ef6bf0

Update app.py

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Files changed (1) hide show
  1. app.py +2 -2
app.py CHANGED
@@ -199,7 +199,7 @@ if __name__ == "__main__":
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  gr.Markdown("<h1 align='center'>Detection and Correction based on Word Importance Ranking (DCWIR) </h1>")
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  gr.Markdown("<h2 align='center'>Clarifications</h2>")
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  gr.Markdown("""
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- - This demo has no mechanism to ensure the adversarial example will be correctly repaired by Rapid. The repair success rate is actually the performance reported in the paper.The user must know the resulted output for sake of demonstration.
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  - The adversarial example and corrected adversarial example may be unnatural to read, while it is because the attackers usually generate unnatural perturbations.
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  - All the proposed attacks are Black Box attack where the attacker has no access to the model parameters.
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  """)
@@ -281,7 +281,7 @@ if __name__ == "__main__":
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  output_adv_label = gr.Textbox(label="Predicted Label of the Adversarial Example")
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  with gr.Row():
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  output_repaired_example = gr.Textbox(
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- label="Repaired Adversarial Example by Rapid"
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  )
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  output_repaired_label = gr.Textbox(label="Predicted Label of the Repaired Adversarial Example")
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  gr.Markdown("<h1 align='center'>Detection and Correction based on Word Importance Ranking (DCWIR) </h1>")
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  gr.Markdown("<h2 align='center'>Clarifications</h2>")
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  gr.Markdown("""
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+ - This demo has no mechanism to ensure the adversarial example will be correctly repaired by DCWIR.
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  - The adversarial example and corrected adversarial example may be unnatural to read, while it is because the attackers usually generate unnatural perturbations.
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  - All the proposed attacks are Black Box attack where the attacker has no access to the model parameters.
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  """)
 
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  output_adv_label = gr.Textbox(label="Predicted Label of the Adversarial Example")
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  with gr.Row():
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  output_repaired_example = gr.Textbox(
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+ label="Repaired Adversarial Example by DCWIR"
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  )
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  output_repaired_label = gr.Textbox(label="Predicted Label of the Repaired Adversarial Example")
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