Privacy-Preserving Reinforcement Learning from Human Feedback via Decoupled Reward Modeling
Fuente:
arXiv
Saved in:
| Main Authors: | Cho, Young Hyun, Sun, Will Wei |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Privacy-Preserving Dynamic Assortment Selection
by: Cho, Young Hyun, et al.
Published: (2024)
by: Cho, Young Hyun, et al.
Published: (2024)
Dense Reward for Free in Reinforcement Learning from Human Feedback
by: Chan, Alex J., et al.
Published: (2024)
by: Chan, Alex J., et al.
Published: (2024)
Privacy Preserving Reinforcement Learning with One-Sided Feedback
by: Cong, Lin William, et al.
Published: (2026)
by: Cong, Lin William, et al.
Published: (2026)
Improving Reinforcement Learning from Human Feedback with Efficient Reward Model Ensemble
by: Zhang, Shun, et al.
Published: (2024)
by: Zhang, Shun, et al.
Published: (2024)
Uncertainty Quantification for Large Language Model Reward Learning under Heterogeneous Human Feedback
by: Liu, Pangpang, et al.
Published: (2025)
by: Liu, Pangpang, et al.
Published: (2025)
Reinforcement Learning from Human Feedback without Reward Inference: Model-Free Algorithm and Instance-Dependent Analysis
by: Zhang, Qining, et al.
Published: (2024)
by: Zhang, Qining, et al.
Published: (2024)
Dual Active Learning for Reinforcement Learning from Human Feedback
by: Liu, Pangpang, et al.
Published: (2024)
by: Liu, Pangpang, et al.
Published: (2024)
Reinforcement Learning from Human Feedback: A Statistical Perspective
by: Liu, Pangpang, et al.
Published: (2026)
by: Liu, Pangpang, et al.
Published: (2026)
Beyond Data Splitting: Full-Data Conformal Prediction by Differential Privacy
by: Cho, Young Hyun, et al.
Published: (2026)
by: Cho, Young Hyun, et al.
Published: (2026)
Off-Policy Corrected Reward Modeling for Reinforcement Learning from Human Feedback
by: Ackermann, Johannes, et al.
Published: (2025)
by: Ackermann, Johannes, et al.
Published: (2025)
Low-Rank Contextual Reinforcement Learning from Heterogeneous Human Feedback
by: Lee, Seong Jin, et al.
Published: (2024)
by: Lee, Seong Jin, et al.
Published: (2024)
A Large Language Model-Driven Reward Design Framework via Dynamic Feedback for Reinforcement Learning
by: Sun, Shengjie, et al.
Published: (2024)
by: Sun, Shengjie, et al.
Published: (2024)
REBEL: Reward Regularization-Based Approach for Robotic Reinforcement Learning from Human Feedback
by: Chakraborty, Souradip, et al.
Published: (2023)
by: Chakraborty, Souradip, et al.
Published: (2023)
Reward-Preserving Attacks For Robust Reinforcement Learning
by: Schott, Lucas, et al.
Published: (2026)
by: Schott, Lucas, et al.
Published: (2026)
Uncertainty-Penalized Reinforcement Learning from Human Feedback with Diverse Reward LoRA Ensembles
by: Zhai, Yuanzhao, et al.
Published: (2023)
by: Zhai, Yuanzhao, et al.
Published: (2023)
Zeroth-Order Policy Gradient for Reinforcement Learning from Human Feedback without Reward Inference
by: Zhang, Qining, et al.
Published: (2024)
by: Zhang, Qining, et al.
Published: (2024)
Gradient Regularization Prevents Reward Hacking in Reinforcement Learning from Human Feedback and Verifiable Rewards
by: Ackermann, Johannes, et al.
Published: (2026)
by: Ackermann, Johannes, et al.
Published: (2026)
When Should an AI Workflow Release? Always-Valid Inference for Black-Box Generate-Verify Systems
by: Cho, Young Hyun, et al.
Published: (2026)
by: Cho, Young Hyun, et al.
Published: (2026)
Reinforcement Learning from Human Feedback
by: Lambert, Nathan
Published: (2025)
by: Lambert, Nathan
Published: (2025)
Online Iterative Reinforcement Learning from Human Feedback with General Preference Model
by: Ye, Chenlu, et al.
Published: (2024)
by: Ye, Chenlu, et al.
Published: (2024)
Privacy-Preserving Personalized Federated Prompt Learning for Multimodal Large Language Models
by: Tran, Linh, et al.
Published: (2025)
by: Tran, Linh, et al.
Published: (2025)
Decoupling Reasoning and Confidence: Resurrecting Calibration in Reinforcement Learning from Verifiable Rewards
by: Ma, Zhengzhao, et al.
Published: (2026)
by: Ma, Zhengzhao, et al.
Published: (2026)
Strategyproof Reinforcement Learning from Human Feedback
by: Buening, Thomas Kleine, et al.
Published: (2025)
by: Buening, Thomas Kleine, et al.
Published: (2025)
Adaptive Querying for Reward Learning from Human Feedback
by: Anand, Yashwanthi, et al.
Published: (2024)
by: Anand, Yashwanthi, et al.
Published: (2024)
Which Rewards Matter? Reward Selection for Reinforcement Learning under Limited Feedback
by: Chaudhari, Shreyas, et al.
Published: (2025)
by: Chaudhari, Shreyas, et al.
Published: (2025)
Privacy Preserving Reinforcement Learning for Population Processes
by: Yang-Zhao, Samuel, et al.
Published: (2024)
by: Yang-Zhao, Samuel, et al.
Published: (2024)
Robust Reinforcement Learning from Corrupted Human Feedback
by: Bukharin, Alexander, et al.
Published: (2024)
by: Bukharin, Alexander, et al.
Published: (2024)
Policy Gradient Primal-Dual Method for Safe Reinforcement Learning from Human Feedback
by: Liu, Qiang, et al.
Published: (2026)
by: Liu, Qiang, et al.
Published: (2026)
DyJR: Preserving Diversity in Reinforcement Learning with Verifiable Rewards via Dynamic Jensen-Shannon Replay
by: Li, Long, et al.
Published: (2026)
by: Li, Long, et al.
Published: (2026)
Reinforcing Human Behavior Simulation via Verbal Feedback
by: Sun, Weiwei, et al.
Published: (2026)
by: Sun, Weiwei, et al.
Published: (2026)
Preserving Expert-Level Privacy in Offline Reinforcement Learning
by: Sharma, Navodita, et al.
Published: (2024)
by: Sharma, Navodita, et al.
Published: (2024)
Sample-Efficient Reinforcement Learning from Human Feedback via Information-Directed Sampling
by: Qi, Han, et al.
Published: (2025)
by: Qi, Han, et al.
Published: (2025)
Exploring Data Scaling Trends and Effects in Reinforcement Learning from Human Feedback
by: Shen, Wei, et al.
Published: (2025)
by: Shen, Wei, et al.
Published: (2025)
Decoupling Task and Behavior: A Two-Stage Reward Curriculum in Reinforcement Learning for Robotics
by: Freitag, Kilian, et al.
Published: (2026)
by: Freitag, Kilian, et al.
Published: (2026)
Reinforcement Learning from Multi-level and Episodic Human Feedback
by: Elahi, Muhammad Qasim, et al.
Published: (2025)
by: Elahi, Muhammad Qasim, et al.
Published: (2025)
A Minimaximalist Approach to Reinforcement Learning from Human Feedback
by: Swamy, Gokul, et al.
Published: (2024)
by: Swamy, Gokul, et al.
Published: (2024)
Multi-turn Reinforcement Learning from Preference Human Feedback
by: Shani, Lior, et al.
Published: (2024)
by: Shani, Lior, et al.
Published: (2024)
Reinforcement Learning with LTL and $ω$-Regular Objectives via Optimality-Preserving Translation to Average Rewards
by: Le, Xuan-Bach, et al.
Published: (2024)
by: Le, Xuan-Bach, et al.
Published: (2024)
Efficient Reinforcement Learning from Human Feedback via Bayesian Preference Inference
by: Cercola, Matteo, et al.
Published: (2025)
by: Cercola, Matteo, et al.
Published: (2025)
Privacy-Preserving Federated Learning via Differential Privacy and Homomorphic Encryption for Cardiovascular Disease Risk Modeling
by: Sharma, Gaurang, et al.
Published: (2026)
by: Sharma, Gaurang, et al.
Published: (2026)
Similar Items
-
Privacy-Preserving Dynamic Assortment Selection
by: Cho, Young Hyun, et al.
Published: (2024) -
Dense Reward for Free in Reinforcement Learning from Human Feedback
by: Chan, Alex J., et al.
Published: (2024) -
Privacy Preserving Reinforcement Learning with One-Sided Feedback
by: Cong, Lin William, et al.
Published: (2026) -
Improving Reinforcement Learning from Human Feedback with Efficient Reward Model Ensemble
by: Zhang, Shun, et al.
Published: (2024) -
Uncertainty Quantification for Large Language Model Reward Learning under Heterogeneous Human Feedback
by: Liu, Pangpang, et al.
Published: (2025)