Fine-tuning Behavioral Cloning Policies with Preference-Based Reinforcement Learning
Fuente:
arXiv
Saved in:
| Main Authors: | Macuglia, Maël, Friedrich, Paul, Ramponi, Giorgia |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Preference Elicitation for Offline Reinforcement Learning
by: Pace, Alizée, et al.
Published: (2024)
by: Pace, Alizée, et al.
Published: (2024)
Contextual Bilevel Reinforcement Learning for Incentive Alignment
by: Thoma, Vinzenz, et al.
Published: (2024)
by: Thoma, Vinzenz, et al.
Published: (2024)
Uncertainty modeling for fine-tuned implicit functions
by: Susmelj, Anna, et al.
Published: (2024)
by: Susmelj, Anna, et al.
Published: (2024)
Human Implicit Preference-Based Policy Fine-tuning for Multi-Agent Reinforcement Learning in USV Swarm
by: Kim, Hyeonjun, et al.
Published: (2025)
by: Kim, Hyeonjun, et al.
Published: (2025)
SelfBC: Self Behavior Cloning for Offline Reinforcement Learning
by: Liu, Shirong, et al.
Published: (2024)
by: Liu, Shirong, et al.
Published: (2024)
Policy Gradient with Tree Search: Avoiding Local Optimas through Lookahead
by: Koren, Uri, et al.
Published: (2025)
by: Koren, Uri, et al.
Published: (2025)
Pragmatic Policy Development via Interpretable Behavior Cloning
by: Matsson, Anton, et al.
Published: (2025)
by: Matsson, Anton, et al.
Published: (2025)
Proximal Action Replacement for Behavior Cloning Actor-Critic in Offline Reinforcement Learning
by: Dong, Jinzong, et al.
Published: (2026)
by: Dong, Jinzong, et al.
Published: (2026)
Fine-tuning Timeseries Predictors Using Reinforcement Learning
by: Cazaux, Hugo, et al.
Published: (2026)
by: Cazaux, Hugo, et al.
Published: (2026)
REFINE-DP: Diffusion Policy Fine-tuning for Humanoid Loco-manipulation via Reinforcement Learning
by: Gu, Zhaoyuan, et al.
Published: (2026)
by: Gu, Zhaoyuan, et al.
Published: (2026)
Behavior Preference Regression for Offline Reinforcement Learning
by: Srinivasan, Padmanaba, et al.
Published: (2025)
by: Srinivasan, Padmanaba, et al.
Published: (2025)
DiffClone: Enhanced Behaviour Cloning in Robotics with Diffusion-Driven Policy Learning
by: Mani, Sabariswaran, et al.
Published: (2024)
by: Mani, Sabariswaran, et al.
Published: (2024)
MAVRL: Learning Reward Functions from Multiple Feedback Types with Amortized Variational Inference
by: Baur, Raphaël, et al.
Published: (2026)
by: Baur, Raphaël, et al.
Published: (2026)
On Feasible Rewards in Multi-Agent Inverse Reinforcement Learning
by: Freihaut, Till, et al.
Published: (2024)
by: Freihaut, Till, et al.
Published: (2024)
Posterior Behavioral Cloning: Pretraining BC Policies for Efficient RL Finetuning
by: Wagenmaker, Andrew, et al.
Published: (2025)
by: Wagenmaker, Andrew, et al.
Published: (2025)
Rate optimal learning of equilibria from data
by: Freihaut, Till, et al.
Published: (2025)
by: Freihaut, Till, et al.
Published: (2025)
SABR: A Stable Adaptive Bitrate Framework Using Behavior Cloning Pretraining and Reinforcement Learning Fine-Tuning
by: Luo, Pengcheng, et al.
Published: (2025)
by: Luo, Pengcheng, et al.
Published: (2025)
Adversarial Policy Optimization for Offline Preference-based Reinforcement Learning
by: Kang, Hyungkyu, et al.
Published: (2025)
by: Kang, Hyungkyu, et al.
Published: (2025)
Preferred-Action-Optimized Diffusion Policies for Offline Reinforcement Learning
by: Zhang, Tianle, et al.
Published: (2024)
by: Zhang, Tianle, et al.
Published: (2024)
Fine-tuning Diffusion Policies with Backpropagation Through Diffusion Timesteps
by: Yang, Ningyuan, et al.
Published: (2025)
by: Yang, Ningyuan, et al.
Published: (2025)
Adaptive Divergence Regularized Policy Optimization for Fine-tuning Generative Models
by: Fan, Jiajun, et al.
Published: (2025)
by: Fan, Jiajun, et al.
Published: (2025)
Ratio-Variance Regularized Policy Optimization for Efficient LLM Fine-tuning
by: Luo, Yu, et al.
Published: (2026)
by: Luo, Yu, et al.
Published: (2026)
Step-wise Adaptive Integration of Supervised Fine-tuning and Reinforcement Learning for Task-Specific LLMs
by: Chen, Jack, et al.
Published: (2025)
by: Chen, Jack, et al.
Published: (2025)
Towards Revealing the Effectiveness of Small-Scale Fine-tuning in R1-style Reinforcement Learning
by: Chen, Yutong, et al.
Published: (2025)
by: Chen, Yutong, et al.
Published: (2025)
Demystifying Design Choices of Reinforcement Fine-tuning: A Batched Contextual Bandit Learning Perspective
by: Xie, Hong, et al.
Published: (2026)
by: Xie, Hong, et al.
Published: (2026)
Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning
by: Alagha, Ahmed, et al.
Published: (2025)
by: Alagha, Ahmed, et al.
Published: (2025)
Diffusion Model-Augmented Behavioral Cloning
by: Chen, Shang-Fu, et al.
Published: (2023)
by: Chen, Shang-Fu, et al.
Published: (2023)
On the Non-decoupling of Supervised Fine-tuning and Reinforcement Learning in Post-training
by: Niu, Xueyan, et al.
Published: (2026)
by: Niu, Xueyan, et al.
Published: (2026)
Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes
by: Kumar, Navdeep, et al.
Published: (2025)
by: Kumar, Navdeep, et al.
Published: (2025)
Behavior-Regularized Diffusion Policy Optimization for Offline Reinforcement Learning
by: Gao, Chen-Xiao, et al.
Published: (2025)
by: Gao, Chen-Xiao, et al.
Published: (2025)
Fine-tuning Pocket-Aware Diffusion Models via Denoising Policy Optimization
by: Xue, Yuan, et al.
Published: (2026)
by: Xue, Yuan, et al.
Published: (2026)
Robust Behavior Cloning Via Global Lipschitz Regularization
by: Wu, Shili, et al.
Published: (2025)
by: Wu, Shili, et al.
Published: (2025)
Self-Predictive Representations for Combinatorial Generalization in Behavioral Cloning
by: Lawson, Daniel, et al.
Published: (2025)
by: Lawson, Daniel, et al.
Published: (2025)
The Importance of Online Data: Understanding Preference Fine-tuning via Coverage
by: Song, Yuda, et al.
Published: (2024)
by: Song, Yuda, et al.
Published: (2024)
Policy-labeled Preference Learning: Is Preference Enough for RLHF?
by: Cho, Taehyun, et al.
Published: (2025)
by: Cho, Taehyun, et al.
Published: (2025)
PB$^2$: Preference Space Exploration via Population-Based Methods in Preference-Based Reinforcement Learning
by: Driss, Brahim, et al.
Published: (2025)
by: Driss, Brahim, et al.
Published: (2025)
Preference Conditioned Multi-Objective Reinforcement Learning: Decomposed, Diversity-Driven Policy Optimization
by: Ambadkar, Tanmay, et al.
Published: (2026)
by: Ambadkar, Tanmay, et al.
Published: (2026)
Search-Based Credit Assignment for Offline Preference-Based Reinforcement Learning
by: Gao, Xiancheng, et al.
Published: (2025)
by: Gao, Xiancheng, et al.
Published: (2025)
Hindsight Preference Learning for Offline Preference-based Reinforcement Learning
by: Gao, Chen-Xiao, et al.
Published: (2024)
by: Gao, Chen-Xiao, et al.
Published: (2024)
When Does Predictive Inverse Dynamics Outperform Behavior Cloning?
by: Schäfer, Lukas, et al.
Published: (2026)
by: Schäfer, Lukas, et al.
Published: (2026)
Similar Items
-
Preference Elicitation for Offline Reinforcement Learning
by: Pace, Alizée, et al.
Published: (2024) -
Contextual Bilevel Reinforcement Learning for Incentive Alignment
by: Thoma, Vinzenz, et al.
Published: (2024) -
Uncertainty modeling for fine-tuned implicit functions
by: Susmelj, Anna, et al.
Published: (2024) -
Human Implicit Preference-Based Policy Fine-tuning for Multi-Agent Reinforcement Learning in USV Swarm
by: Kim, Hyeonjun, et al.
Published: (2025) -
SelfBC: Self Behavior Cloning for Offline Reinforcement Learning
by: Liu, Shirong, et al.
Published: (2024)