SALT-NLP/search_privacy_risk
Searching for Privacy Risks in LLM Agents via Simulation Paper, Code Authors: Yanzhe Zhang, Diyi Yang Abstract The widespread deployment of LLM-based agents is likely to introduce a critical privacy threat: malicious agents that proactively engage others in multi-turn interactions to extract sensitive information. These dynamic dialogues enable adaptive attack strategies that can cause severe privacy violations, yet their evolving nature makes it difficult to… See the full description on the dataset page: https://huggingface.co/datasets/SALT-NLP/search_privacy_risk.
| Author / organization | SALT-NLP |
|---|---|
| License (as declared) | mit |
| Downloads | 1.2K (as reported by Hugging Face) |
| Likes | 1 |
| Created | 13 August 2025 |
| Last updated at source | 15 August 2025 |
Popularity, last 3 days
1,203 now (-364 since 2026-10-16). Counts as reported by the source, snapshotted daily by Silytics.
Recent changes
- 16 Oct 2026 Description: Searching for Privacy Risks in LLM Agents via Simulation Paper, Code Authors: Yanzhe Zhang, Diyi Yang Abstract The widespread deployment of LLM-based agents is likely to introduce a critical privacy threat: malicious agents that proactively → Searching for Privacy Risks in LLM Agents via Simulation Paper, Code Authors: Yanzhe Zhang, Diyi Yang Abstract The widespread deployment of LLM-based agents is likely to introduce a critical privacy threat: malicious agents that proactively
Changes detected by Silytics between refreshes of the source.
More from SALT-NLP
- SALT-NLP/SWE-chatDataset
- SALT-NLP/hleDataset
- SALT-NLP/cogym-collabskill-trajectoriesDataset
- SALT-NLP/cogym-real-trajectoriesDataset
- SALT-NLP/hle-tgtDataset
- SALT-NLP/Design2CodeDataset
Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 18 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.