Under linear-model assumptions, offline RLHF and DPO both reduce to logistic regression, and privatizing labels before corruption (LTC) carries an extra c(ε) factor in the error bounds compared to corrupting before privatizing (CTL).
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
A Unified Theoretical Analysis of Private and Robust Offline Alignment: from RLHF to DPO
Under linear-model assumptions, offline RLHF and DPO both reduce to logistic regression, and privatizing labels before corruption (LTC) carries an extra c(ε) factor in the error bounds compared to corrupting before privatizing (CTL).