Robust Conversational Agents against Imperceptible Toxicity Triggers (2022.naacl-main)
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| Challenge: | Existing work to generate adversarial attacks is costly and not scalable . despite the abundance of research in this area, little attention has been given to adversarials . |
| Approach: | They propose an adversarial attack mechanism that mitigates toxic language generation . they propose a defense mechanism that is scalable and can be generalized . |
| Outcome: | The proposed defense is effective at avoiding toxic language generation even against imperceptible toxicity triggers while preserving conversational flow. |
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Johannes Welbl, Amelia Glaese, Jonathan Uesato, Sumanth Dathathri, John Mellor, Lisa Anne Hendricks, Kirsty Anderson, Pushmeet Kohli, Ben Coppin, Po-Sen Huang
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