Papers by Ziqing Huang
Poisoning Retrieval Corpora by Injecting Adversarial Passages (2023.emnlp-main)
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| Challenge: | Dense retrievers have outperformed traditional lexical methods in a range of information retrieval tasks, but to what extent can they be safely deployed in real-world applications? |
| Approach: | They propose a method where a malicious user injects a small number of adversarial passages into a retrieval corpus to maximize similarity with a set of training queries. |
| Outcome: | The proposed attack fools retrieval systems into returning top results for queries not seen by the attacker. |