Effectiveness of Privacy-preserving Algorithms in LLMs: A Benchmark and Empirical Analysis.
Jinglin Sun|Basem Suleiman|Imdad Ullah|Imran Razzak
| Anthology ID: | DBLP:conf/www/SunSUR25 |
|---|---|
| Volume: | Proceedings of the ACM on Web Conference 2025, WWW 2025, Sydney, NSW, Australia, 28 April 2025- 2 May 2025 |
| Year: | 2025 |
| Venue: | The Web Conference (WWW) |
| Publisher: | ACM |
| Pages: | 5224-5233 |
| URL: | https://doi.org/10.1145/3696410.3714531 |
| DOI: | https://doi.org/10.1145/3696410.3714531 |
| DBLP: | conf/www/SunSUR25 |
| BibTeX: |
@inproceedings{sun-2025-effectiveness,
author = {Jinglin Sun and
Basem Suleiman and
Imdad Ullah and
Imran Razzak},
editor = {Guodong Long and
Michale Blumestein and
Yi Chang and
Liane Lewin-Eytan and
Zi Huang and
Elad Yom-Tov},
title = {{Effectiveness of Privacy-preserving Algorithms in LLMs: A Benchmark and Empirical Analysis}},
booktitle = {{Proceedings of the ACM on Web Conference 2025, WWW 2025, Sydney, NSW, Australia, 28 April 2025- 2 May 2025}},
pages = {5224--5233},
publisher = {ACM},
year = {2025},
url = {https://doi.org/10.1145/3696410.3714531},
doi = {https://doi.org/10.1145/3696410.3714531}
}