Cover Image

Low-Rank Adaptation for Critic Learning in Off-Policy Reinforcement Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhuang, Yuan, Bian, Yuexin, He, Sihong, Feng, Jie, Su, Qing, Han, Songyang, Petit, Jonathan, Ji, Shihao, Shi, Yuanyuan, Miao, Fei
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

LD-MoLE: Learnable Dynamic Routing for Mixture of LoRA Experts
by: Zhuang, Yuan, et al.
Published: (2025)

DiffOP: Reinforcement Learning of Optimization-Based Control Policies via Implicit Policy Gradients
by: Bian, Yuexin, et al.
Published: (2024)

RN-D: Discretized Categorical Actors with Regularized Networks for On-Policy Reinforcement Learning
by: Bian, Yuexin, et al.
Published: (2026)

What is the Solution for State-Adversarial Multi-Agent Reinforcement Learning?
by: Han, Songyang, et al.
Published: (2022)

Adaptive Inverse Reinforcement Learning with Online Off-Policy Data Collection
by: Li, Yibei, et al.
Published: (2025)

Constrained Reinforcement Learning Under Model Mismatch
by: Sun, Zhongchang, et al.
Published: (2024)

Unsqueeze [CLS] Bottleneck to Learn Rich Representations
by: Su, Qing, et al.
Published: (2024)

Off-Dynamics Reinforcement Learning via Domain Adaptation and Reward Augmented Imitation
by: Guo, Yihong, et al.
Published: (2024)

L-MoE: End-to-End Training of a Lightweight Mixture of Low-Rank Adaptation Experts
by: Ji, Shihao, et al.
Published: (2025)

Towards Off-Policy Reinforcement Learning for Ranking Policies with Human Feedback
by: Xiao, Teng, et al.
Published: (2024)

Operator learning for energy-efficient building ventilation control with computational fluid dynamics simulation of a real-world classroom
by: Bian, Yuexin, et al.
Published: (2025)

Momentum for the Win: Collaborative Federated Reinforcement Learning across Heterogeneous Environments
by: Wang, Han, et al.
Published: (2024)

Toward Value-oriented Renewable Energy Forecasting: An Iterative Learning Approach
by: Zhang, Yufan, et al.
Published: (2023)

On the Reuse Bias in Off-Policy Reinforcement Learning
by: Ying, Chengyang, et al.
Published: (2022)

Pessimistic Off-Policy Optimization for Learning to Rank
by: Cief, Matej, et al.
Published: (2022)

Compressible Dynamics in Deep Overparameterized Low-Rank Learning & Adaptation
by: Yaras, Can, et al.
Published: (2024)

PDE Control Gym: A Benchmark for Data-Driven Boundary Control of Partial Differential Equations
by: Bhan, Luke, et al.
Published: (2024)

Improving Sequential Market Coordination via Value-oriented Renewable Energy Forecasting
by: Zhang, Yufan, et al.
Published: (2024)

SLowRL: Safe Low-Rank Adaptation Reinforcement Learning for Locomotion
by: Daneshmand, Elham, et al.
Published: (2026)

Efficient Policy Adaptation for Voltage Control Under Unknown Topology Changes
by: Feng, Jie, et al.
Published: (2026)

Ventilation and Temperature Control for Energy-efficient and Healthy Buildings: A Differentiable PDE Approach
by: Bian, Yuexin, et al.
Published: (2024)

YOLO-MARL: You Only LLM Once for Multi-Agent Reinforcement Learning
by: Zhuang, Yuan, et al.
Published: (2024)

Optimal Policy Sparsification and Low Rank Decomposition for Deep Reinforcement Learning
by: Goddla, Vikram
Published: (2024)

Off Policy Lyapunov Stability in Reinforcement Learning
by: Gill, Sarvan, et al.
Published: (2025)

Low-Rank Agent-Specific Adaptation (LoRASA) for Multi-Agent Policy Learning
by: Zhang, Beining, et al.
Published: (2025)

Provable Meta-Learning with Low-Rank Adaptations
by: Block, Jacob L., et al.
Published: (2024)

Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning
by: Rozada, Sergio, et al.
Published: (2025)

CUQDS: Conformal Uncertainty Quantification under Distribution Shift for Trajectory Prediction
by: Huang, Huiqun, et al.
Published: (2024)

Predicting Strategic Energy Storage Behaviors
by: Bian, Yuexin, et al.
Published: (2023)

Off-Policy Primal-Dual Safe Reinforcement Learning
by: Wu, Zifan, et al.
Published: (2024)

Off-Policy Correction For Multi-Agent Reinforcement Learning
by: Zawalski, Michał, et al.
Published: (2021)

Off-Policy Reinforcement Learning with High Dimensional Reward
by: Lee, Dong Neuck, et al.
Published: (2024)

Frugal Actor-Critic: Sample Efficient Off-Policy Deep Reinforcement Learning Using Unique Experiences
by: Singh, Nikhil Kumar, et al.
Published: (2024)

AdaPreLoRA: Adafactor Preconditioned Low-Rank Adaptation
by: Liu, Ziyun, et al.
Published: (2026)

Off-Policy Value-Based Reinforcement Learning for Large Language Models
by: Wang, Peng-Yuan, et al.
Published: (2026)

Energy-Structured Low-Rank Adaptation for Continual Learning
by: Li, Longhua, et al.
Published: (2026)

Selective Aggregation for Low-Rank Adaptation in Federated Learning
by: Guo, Pengxin, et al.
Published: (2024)

Preventing Rank Collapse in Federated Low-Rank Adaptation with Client Heterogeneity
by: Wu, Fei, et al.
Published: (2026)

MokA: Multimodal Low-Rank Adaptation for MLLMs
by: Wei, Yake, et al.
Published: (2025)

PLAN: Proactive Low-Rank Allocation for Continual Learning
by: Wang, Xiequn, et al.
Published: (2025)