Papers with Retrieval-Augmented Generation based agentic applications
Exploiting the Shadows: Unveiling Privacy Leaks through Lower-Ranked Tokens in Large Language Models (2025.acl-long)
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| Challenge: | Large language models face vulnerabilities related to the extraction of sensitive information. |
| Approach: | They propose a method to exploit the model's lower-ranked output tokens to extract private information from retrieved documents or training knowledge. |
| Outcome: | The proposed method is effective in both the agentic application privacy extraction setting and the direct training data extraction. |