Cover Image

APLOT: Robust Reward Modeling via Adaptive Preference Learning with Optimal Transport

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Li, Zhuo, Feng, Yuege, Guo, Dandan, Hu, Jinpeng, Gao, Anningzhe, Wan, Xiang
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

RLHF in an SFT Way: From Optimal Solution to Reward-Weighted Alignment
by: Du, Yuhao, et al.
Published: (2025)

Eliminating Inductive Bias in Reward Models with Information-Theoretic Guidance
by: Li, Zhuo, et al.
Published: (2025)

Optimal Transport for LLM Reward Modeling from Noisy Preference
by: Pan, Licheng, et al.
Published: (2026)

Self-Instructed Derived Prompt Generation Meets In-Context Learning: Unlocking New Potential of Black-Box LLMs
by: Li, Zhuo, et al.
Published: (2024)

In-Context Reward Adaptation for Robust Preference Modeling
by: Sun, Zhenyu, et al.
Published: (2026)

Distributional Process Reward Models: Calibrated Prediction of Future Rewards via Conditional Optimal Transport
by: Ma, Rachel, et al.
Published: (2026)

AMoPO: Adaptive Multi-objective Preference Optimization without Reward Models and Reference Models
by: Liu, Qi, et al.
Published: (2025)

AlphaDPO: Adaptive Reward Margin for Direct Preference Optimization
by: Wu, Junkang, et al.
Published: (2024)

Robot Policy Learning with Temporal Optimal Transport Reward
by: Fu, Yuwei, et al.
Published: (2024)

Similarity as Reward Alignment: Robust and Versatile Preference-based Reinforcement Learning
by: Rajaram, Sara, et al.
Published: (2025)

IRPM: Intergroup Relative Preference Modeling for Pointwise Generative Reward Models
by: Song, Haonan, et al.
Published: (2026)

Margin Adaptive DPO: Leveraging Reward Model for Granular Control in Preference Optimization
by: Rho, Hyung Gyu
Published: (2025)

Causally Robust Reward Learning from Reason-Augmented Preference Feedback
by: Hwang, Minjune, et al.
Published: (2026)

PaTaRM: Bridging Pairwise and Pointwise Signals via Preference-Aware Task-Adaptive Reward Modeling
by: Jian, Ai, et al.
Published: (2025)

Reward Learning From Preference With Ties
by: Liu, Jinsong, et al.
Published: (2024)

Add-One-In: Incremental Sample Selection for Large Language Models via a Choice-Based Greedy Paradigm
by: Li, Zhuo, et al.
Published: (2025)

CoD, Towards an Interpretable Medical Agent using Chain of Diagnosis
by: Chen, Junying, et al.
Published: (2024)

Residual Reward Models for Preference-based Reinforcement Learning
by: Cao, Chenyang, et al.
Published: (2025)

Preference-Based Self-Distillation: Beyond KL Matching via Reward Regularization
by: Yu, Xin, et al.
Published: (2026)

Preference Poisoning Attacks on Reward Model Learning
by: Wu, Junlin, et al.
Published: (2024)

Optimal Transport Perturbations for Safe Reinforcement Learning with Robustness Guarantees
by: Queeney, James, et al.
Published: (2023)

Reward Models in Deep Reinforcement Learning: A Survey
by: Yu, Rui, et al.
Published: (2025)

Rectifying Shortcut Behaviors in Preference-based Reward Learning
by: Ye, Wenqian, et al.
Published: (2025)

Exploring and Addressing Reward Confusion in Offline Preference Learning
by: Chen, Xin, et al.
Published: (2024)

Preference as Reward, Maximum Preference Optimization with Importance Sampling
by: Jiang, Zaifan, et al.
Published: (2023)

TimeRewarder: Learning Dense Reward from Passive Videos via Frame-wise Temporal Distance
by: Liu, Yuyang, et al.
Published: (2025)

Larger or Smaller Reward Margins to Select Preferences for Alignment?
by: Huang, Kexin, et al.
Published: (2025)

Listwise Reward Estimation for Offline Preference-based Reinforcement Learning
by: Choi, Heewoong, et al.
Published: (2024)

Robust Offline Reinforcement learning with Heavy-Tailed Rewards
by: Zhu, Jin, et al.
Published: (2023)

A Riemannian Approach to Ground Metric Learning for Optimal Transport
by: Jawanpuria, Pratik, et al.
Published: (2024)

COPR: Continual Human Preference Learning via Optimal Policy Regularization
by: Zhang, Han, et al.
Published: (2024)

PARM: Multi-Objective Test-Time Alignment via Preference-Aware Autoregressive Reward Model
by: Lin, Baijiong, et al.
Published: (2025)

Adversarial Preference Learning for Robust LLM Alignment
by: Wang, Yuanfu, et al.
Published: (2025)

$ξ$-DPO: Direct Preference Optimization via Ratio Reward Margin
by: Fan, Zhengyuan, et al.
Published: (2026)

Safeguarding LLM Fine-tuning via Push-Pull Distributional Alignment
by: Wang, Haozhong, et al.
Published: (2026)

Sample-Efficient Preference-based Reinforcement Learning with Dynamics Aware Rewards
by: Metcalf, Katherine, et al.
Published: (2024)

Learning Pareto-Optimal Rewards from Noisy Preferences: A Framework for Multi-Objective Inverse Reinforcement Learning
by: Cherukuri, Kalyan, et al.
Published: (2025)

Auto-Rubric: Learning From Implicit Weights to Explicit Rubrics for Reward Modeling
by: Xie, Lipeng, et al.
Published: (2025)

Adaptive and Robust DBSCAN with Multi-agent Reinforcement Learning
by: Peng, Hao, et al.
Published: (2025)

Cross-Domain Imitation Learning via Optimal Transport
by: Fickinger, Arnaud, et al.
Published: (2021)