Cover Image

Trust Region Reward Optimization and Proximal Inverse Reward Optimization Algorithm

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Chen, Yang, Zou, Menglin, Zhang, Jiaqi, Zhang, Yitan, Yang, Junyi, Gendron, Gael, Zhang, Libo, Liu, Jiamou, Witbrock, Michael J.
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

Inferring Reward Machines and Transition Machines from Partially Observable Markov Decision Processes
by: Wu, Yuly, et al.
Published: (2025)

Adversarial Inverse Reinforcement Learning for Mean Field Games
by: Chen, Yang, et al.
Published: (2021)

Meta-Inverse Reinforcement Learning for Mean Field Games via Probabilistic Context Variables
by: Chen, Yang, et al.
Published: (2025)

ORSO: Accelerating Reward Design via Online Reward Selection and Policy Optimization
by: Zhang, Chen Bo Calvin, et al.
Published: (2024)

Assessing and Enhancing the Robustness of Large Language Models with Task Structure Variations for Logical Reasoning
by: Bao, Qiming, et al.
Published: (2023)

Pretrain Value, Not Reward: Decoupled Value Policy Optimization
by: Huang, Chenghua, et al.
Published: (2025)

PPO-BR: Dual-Signal Entropy-Reward Adaptation for Trust Region Policy Optimization
by: Rahman, Ben
Published: (2025)

Overcoming Reward Overoptimization via Adversarial Policy Optimization with Lightweight Uncertainty Estimation
by: Zhang, Xiaoying, et al.
Published: (2024)

Intrinsic Reward Policy Optimization for Sparse-Reward Environments
by: Cho, Minjae, et al.
Published: (2026)

DRPO: Efficient Reasoning via Decoupled Reward Policy Optimization
by: Li, Gang, et al.
Published: (2025)

Optimas: Optimizing Compound AI Systems with Globally Aligned Local Rewards
by: Wu, Shirley, et al.
Published: (2025)

Accelerating Proximal Policy Optimization Learning Using Task Prediction for Solving Environments with Delayed Rewards
by: Ahmad, Ahmad, et al.
Published: (2024)

Fairness Aware Reward Optimization
by: Choi, Ching Lam, et al.
Published: (2026)

PerPO: Perceptual Preference Optimization via Discriminative Rewarding
by: Zhu, Zining, et al.
Published: (2025)

Mitigating Reward Over-Optimization in RLHF via Behavior-Supported Regularization
by: Dai, Juntao, et al.
Published: (2025)

Assigning Credit with Partial Reward Decoupling in Multi-Agent Proximal Policy Optimization
by: Kapoor, Aditya, et al.
Published: (2024)

PRDP: Proximal Reward Difference Prediction for Large-Scale Reward Finetuning of Diffusion Models
by: Deng, Fei, et al.
Published: (2024)

T-REG: Preference Optimization with Token-Level Reward Regularization
by: Zhou, Wenxuan, et al.
Published: (2024)

RiskPO: Risk-based Policy Optimization via Verifiable Reward for LLM Post-Training
by: Ren, Tao, et al.
Published: (2025)

Causal Cartographer: From Mapping to Reasoning Over Counterfactual Worlds
by: Gendron, Gaël, et al.
Published: (2025)

IR$^3$: Contrastive Inverse Reinforcement Learning for Interpretable Detection and Mitigation of Reward Hacking
by: Beigi, Mohammad, et al.
Published: (2026)

Reward-Augmented Data Enhances Direct Preference Alignment of LLMs
by: Zhang, Shenao, et al.
Published: (2024)

ExO-PPO: an Extended Off-policy Proximal Policy Optimization Algorithm
by: Wang, Hanyong, et al.
Published: (2026)

Planning-Augmented Sampling with Early Guidance for High-Reward Discovery
by: Zhu, Rui, et al.
Published: (2025)

From Demonstrations to Rewards: Test-Time Prompt Optimization for VLM Reward Models
by: Gumbsch, Christian, et al.
Published: (2026)

GOPO: Policy Optimization using Ranked Rewards
by: Choi, Kyuseong, et al.
Published: (2026)

Beyond Reward Hacking: Causal Rewards for Large Language Model Alignment
by: Wang, Chaoqi, et al.
Published: (2025)

Selective Preference Optimization via Token-Level Reward Function Estimation
by: Yang, Kailai, et al.
Published: (2024)

Inverse Reinforcement Learning with Dynamic Reward Scaling for LLM Alignment
by: Cheng, Ruoxi, et al.
Published: (2025)

Inverse Reinforcement Learning without an Optimal Demonstrator: A Feasible Reward Set Approach
by: Kim, Kihyun, et al.
Published: (2026)

Defeasible Visual Entailment: Benchmark, Evaluator, and Reward-Driven Optimization
by: Zhang, Yue, et al.
Published: (2024)

HPO: Hysteretic Policy Optimization for Stable and Efficient Training under Sparse-Reward Regime
by: Sana, Mohamed, et al.
Published: (2026)

Trusted Weights, Treacherous Optimizations? Optimization-Triggered Backdoor Attacks on LLMs
by: Wang, Yifei, et al.
Published: (2026)

TrasMuon: Trust-Region Adaptive Scaling for Orthogonalized Momentum Optimizers
by: Cheng, Peng, et al.
Published: (2026)

Adversarial Reward Auditing for Active Detection and Mitigation of Reward Hacking
by: Beigi, Mohammad, et al.
Published: (2026)

TW-CRL: Time-Weighted Contrastive Reward Learning for Efficient Inverse Reinforcement Learning
by: Li, Yuxuan, et al.
Published: (2025)

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

Value-Free Policy Optimization via Reward Partitioning
by: Faye, Bilal, et al.
Published: (2025)

PRPO: Aligning Process Reward with Outcome Reward in Policy Optimization
by: Ding, Ruiyi, et al.
Published: (2026)

InfoRM: Mitigating Reward Hacking in RLHF via Information-Theoretic Reward Modeling
by: Miao, Yuchun, et al.
Published: (2024)