Cover Image

In-Context Compositional Q-Learning for Offline Reinforcement Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Xu, Qiushui, Huang, Yuhao, Jiang, Yushu, Song, Lei, Wang, Jinyu, Zheng, Wenliang, Bian, Jiang
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

Unveiling Markov Heads in Pretrained Language Models for Offline Reinforcement Learning
by: Zhao, Wenhao, et al.
Published: (2024)

Mildly Constrained Evaluation Policy for Offline Reinforcement Learning
by: Xu, Linjie, et al.
Published: (2023)

Imagination-Limited Q-Learning for Offline Reinforcement Learning
by: Liu, Wenhui, et al.
Published: (2025)

Higher Replay Ratio Empowers Sample-Efficient Multi-Agent Reinforcement Learning
by: Xu, Linjie, et al.
Published: (2024)

Adaptive Neighborhood-Constrained Q Learning for Offline Reinforcement Learning
by: Mao, Yixiu, et al.
Published: (2025)

Learning to Select In-Context Demonstration Preferred by Large Language Model
by: Zhang, Zheng, et al.
Published: (2025)

Mildly Conservative Q-Learning for Offline Reinforcement Learning
by: Lyu, Jiafei, et al.
Published: (2022)

Offline Reinforcement Learning with Imbalanced Datasets
by: Jiang, Li, et al.
Published: (2023)

The Generalization Gap in Offline Reinforcement Learning
by: Mediratta, Ishita, et al.
Published: (2023)

Variational OOD State Correction for Offline Reinforcement Learning
by: Jiang, Ke, et al.
Published: (2025)

Doubly Mild Generalization for Offline Reinforcement Learning
by: Mao, Yixiu, et al.
Published: (2024)

ENOTO: Improving Offline-to-Online Reinforcement Learning with Q-Ensembles
by: Zhao, Kai, et al.
Published: (2023)

Exclusively Penalized Q-learning for Offline Reinforcement Learning
by: Yeom, Junghyuk, et al.
Published: (2024)

Model-based Offline Reinforcement Learning with Lower Expectile Q-Learning
by: Park, Kwanyoung, et al.
Published: (2024)

Offline Reinforcement Learning in Large State Spaces: Algorithms and Guarantees
by: Jiang, Nan, et al.
Published: (2025)

Compositional Conservatism: A Transductive Approach in Offline Reinforcement Learning
by: Song, Yeda, et al.
Published: (2024)

Causal Flow Q-Learning for Robust Offline Reinforcement Learning
by: Li, Mingxuan, et al.
Published: (2026)

ACL-QL: Adaptive Conservative Level in Q-Learning for Offline Reinforcement Learning
by: Wu, Kun, et al.
Published: (2024)

PIQL: Projective Implicit Q-Learning with Support Constraint for Offline Reinforcement Learning
by: Han, Xinchen, et al.
Published: (2025)

Improving Offline-to-Online Reinforcement Learning with Q Conditioned State Entropy Exploration
by: Zhang, Ziqi, et al.
Published: (2023)

On the Complexity of Offline Reinforcement Learning with $Q^\star$-Approximation and Partial Coverage
by: Liu, Haolin, et al.
Published: (2026)

FORLER: Federated Offline Reinforcement Learning with Q-Ensemble and Actor Rectification
by: Qiao, Nan, et al.
Published: (2026)

MG-TSD: Multi-Granularity Time Series Diffusion Models with Guided Learning Process
by: Fan, Xinyao, et al.
Published: (2024)

Holdout-Loss-Based Data Selection for LLM Finetuning via In-Context Learning
by: Zhang, Ling, et al.
Published: (2025)

Pretraining a Shared Q-Network for Data-Efficient Offline Reinforcement Learning
by: Park, Jongchan, et al.
Published: (2025)

Safe Flow Q-Learning: Offline Safe Reinforcement Learning with Reachability-Based Flow Policies
by: Tayal, Mumuksh, et al.
Published: (2026)

Robotic Manipulation Datasets for Offline Compositional Reinforcement Learning
by: Hussing, Marcel, et al.
Published: (2023)

SeqRoute: Global Budget-Aware Sequential LLM Routing via Offline Reinforcement Learning
by: Xu, Zhongling, et al.
Published: (2026)

FlowQ: Energy-Guided Flow Policies for Offline Reinforcement Learning
by: Alles, Marvin, et al.
Published: (2025)

Tackling Data Corruption in Offline Reinforcement Learning via Sequence Modeling
by: Xu, Jiawei, et al.
Published: (2024)

Offline Trajectory Optimization for Offline Reinforcement Learning
by: Zhao, Ziqi, et al.
Published: (2024)

Adaptive Replay Buffer for Offline-to-Online Reinforcement Learning
by: Song, Chihyeon, et al.
Published: (2025)

Proximal Action Replacement for Behavior Cloning Actor-Critic in Offline Reinforcement Learning
by: Dong, Jinzong, et al.
Published: (2026)

Offline-to-Online Reinforcement Learning with Classifier-Free Diffusion Generation
by: Huang, Xiao, et al.
Published: (2025)

SPEQ: Offline Stabilization Phases for Efficient Q-Learning in High Update-To-Data Ratio Reinforcement Learning
by: Romeo, Carlo, et al.
Published: (2025)

OPRIDE: Offline Preference-based Reinforcement Learning via In-Dataset Exploration
by: Yang, Yiqin, et al.
Published: (2026)

Two-Step Offline Preference-Based Reinforcement Learning with Constrained Actions
by: Xu, Yinglun, et al.
Published: (2023)

Mutual Information Regularized Offline Reinforcement Learning
by: Ma, Xiao, et al.
Published: (2022)

Towards Robust Offline Reinforcement Learning under Diverse Data Corruption
by: Yang, Rui, et al.
Published: (2023)

Yes, Q-learning Helps Offline In-Context RL
by: Tarasov, Denis, et al.
Published: (2025)