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PPT: Backdoor Attacks on Pre-trained Models via Poisoned Prompt Tuning

Research article (Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022) · cited 31× · AI/ML
academia openalex:W4285603001
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PPT: Backdoor Attacks on Pre-trained Models via Poisoned Prompt Tuning

Summary

PPT: Backdoor Attacks on Pre-trained Models via Poisoned Prompt Tuning is a scholarly article[1].

Key Facts

  • PPT: Backdoor Attacks on Pre-trained Models via Poisoned Prompt Tuning's instance of is recorded as scholarly article[2].

References

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Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). PPT: Backdoor Attacks on Pre-trained Models via Poisoned Prompt Tuning. Retrieved May 24, 2026, from https://4ort.xyz/entity/ppt-backdoor-attacks-on-pre-trained-models-via-poisoned-prompt-tuning
MLA “PPT: Backdoor Attacks on Pre-trained Models via Poisoned Prompt Tuning.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/ppt-backdoor-attacks-on-pre-trained-models-via-poisoned-prompt-tuning.
BibTeX @misc{4ortxyz_ppt-backdoor-attacks-on-pre-trained-models-via-poisoned-prompt-tuning_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{PPT: Backdoor Attacks on Pre-trained Models via Poisoned Prompt Tuning}}, year = {2026}, url = {https://4ort.xyz/entity/ppt-backdoor-attacks-on-pre-trained-models-via-poisoned-prompt-tuning}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): PPT: Backdoor Attacks on Pre-trained Models via Poisoned Prompt Tuning — https://4ort.xyz/entity/ppt-backdoor-attacks-on-pre-trained-models-via-poisoned-prompt-tuning (retrieved 2026-05-24)

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