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KL-regularization Itself is Differentially Private in Bandits and RLHF
v1v2 (latest)

KL-regularization Itself is Differentially Private in Bandits and RLHF

23 May 2025
Yizhou Zhang
Kishan Panaganti
Laixi Shi
Juba Ziani
Adam Wierman
ArXiv (abs)PDFHTML

Papers citing "KL-regularization Itself is Differentially Private in Bandits and RLHF"

4 / 4 papers shown
Offline and Online KL-Regularized RLHF under Differential Privacy
Offline and Online KL-Regularized RLHF under Differential Privacy
Yulian Wu
Rushil Thareja
Praneeth Vepakomma
Francesco Orabona
OffRL
117
0
0
15 Oct 2025
Towards User-level Private Reinforcement Learning with Human Feedback
Towards User-level Private Reinforcement Learning with Human Feedback
Jing Zhang
Mingxi Lei
Meng Ding
Mengdi Li
Zihang Xiang
Difei Xu
Jinhui Xu
Di Wang
258
6
0
22 Feb 2025
Differentially Private Policy Gradient
Differentially Private Policy Gradient
Alexandre Rio
M. Barlier
Igor Colin
OffRL
275
2
0
31 Jan 2025
Sharp Analysis for KL-Regularized Contextual Bandits and RLHF
Sharp Analysis for KL-Regularized Contextual Bandits and RLHF
Heyang Zhao
Chenlu Ye
Quanquan Gu
Tong Zhang
OffRL
556
13
0
07 Nov 2024
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