:: Library Catalog

Copertina

Salvato in:

Dettagli Bibliografici
Autori principali:	Lei, Xing, Wang, Jincheng, Zhang, Xuetao, Wang, Donglin
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Machine Learning
Accesso online:	https://arxiv.org/abs/2605.01862
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

MGDA: Model-based Goal Data Augmentation for Offline Goal-conditioned Weighted Supervised Learning
di: Lei, Xing, et al.
Pubblicazione: (2024)

Q-WSL: Optimizing Goal-Conditioned RL with Weighted Supervised Learning via Dynamic Programming
di: Lei, Xing, et al.
Pubblicazione: (2024)

GCHR : Goal-Conditioned Hindsight Regularization for Sample-Efficient Reinforcement Learning
di: Lei, Xing, et al.
Pubblicazione: (2025)

Efficient Hierarchical Implicit Flow Q-learning for Offline Goal-conditioned Reinforcement Learning
di: Dong, Zhiqiang, et al.
Pubblicazione: (2026)

Reachability Weighted Offline Goal-conditioned Resampling
di: Yang, Wenyan, et al.
Pubblicazione: (2025)

Reinformer: Max-Return Sequence Modeling for Offline RL
di: Zhuang, Zifeng, et al.
Pubblicazione: (2024)

Goal-conditioned Offline Reinforcement Learning through State Space Partitioning
di: Wang, Mianchu, et al.
Pubblicazione: (2023)

Offline Goal-conditioned Reinforcement Learning with Quasimetric Representations
di: Myers, Vivek, et al.
Pubblicazione: (2025)

Towards Efficient and Expressive Offline RL via Flow-Anchored Noise-conditioned Q-Learning
di: Lee, Sungyoung, et al.
Pubblicazione: (2026)

Closing the Gap between TD Learning and Supervised Learning with $Q$-Conditioned Maximization
di: Lei, Xing, et al.
Pubblicazione: (2025)

GOPlan: Goal-conditioned Offline Reinforcement Learning by Planning with Learned Models
di: Wang, Mianchu, et al.
Pubblicazione: (2023)

Demystifying the Mechanisms Behind Emergent Exploration in Goal-conditioned RL
di: Bastankhah, Mahsa, et al.
Pubblicazione: (2025)

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

OGBench: Benchmarking Offline Goal-Conditioned RL
di: Park, Seohong, et al.
Pubblicazione: (2024)

Balancing Signal and Variance: Adaptive Offline RL Post-Training for VLA Flow Models
di: Zhang, Hongyin, et al.
Pubblicazione: (2025)

When Are RL Hyperparameters Benign? A Study in Offline Goal-Conditioned RL
di: Töpperwien, Jan Malte, et al.
Pubblicazione: (2026)

Chain-of-Goals Hierarchical Policy for Long-Horizon Offline Goal-Conditioned RL
di: Choi, Jinwoo, et al.
Pubblicazione: (2026)

Efficient Online RL Fine Tuning with Offline Pre-trained Policy Only
di: Xiao, Wei, et al.
Pubblicazione: (2025)

OER: Offline Experience Replay for Continual Offline Reinforcement Learning
di: Gai, Sibo, et al.
Pubblicazione: (2023)

Data-Incremental Continual Offline Reinforcement Learning
di: Gai, Sibo, et al.
Pubblicazione: (2024)

A Real-World Quadrupedal Locomotion Benchmark for Offline Reinforcement Learning
di: Zhang, Hongyin, et al.
Pubblicazione: (2023)

Q-value Regularized Transformer for Offline Reinforcement Learning
di: Hu, Shengchao, et al.
Pubblicazione: (2024)

HIQL: Offline Goal-Conditioned RL with Latent States as Actions
di: Park, Seohong, et al.
Pubblicazione: (2023)

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

Behavior-Adaptive Q-Learning: A Unifying Framework for Offline-to-Online RL
di: Zu, Lipeng, et al.
Pubblicazione: (2025)

DIDI: Diffusion-Guided Diversity for Offline Behavioral Generation
di: Liu, Jinxin, et al.
Pubblicazione: (2024)

Stabilizing Contrastive RL: Techniques for Robotic Goal Reaching from Offline Data
di: Zheng, Chongyi, et al.
Pubblicazione: (2023)

Making Offline RL Online: Collaborative World Models for Offline Visual Reinforcement Learning
di: Wang, Qi, et al.
Pubblicazione: (2023)

GEVRM: Goal-Expressive Video Generation Model For Robust Visual Manipulation
di: Zhang, Hongyin, et al.
Pubblicazione: (2025)

Augmenting Offline RL with Unlabeled Data
di: Wang, Zhao, et al.
Pubblicazione: (2024)

In-Context Compositional Q-Learning for Offline Reinforcement Learning
di: Xu, Qiushui, et al.
Pubblicazione: (2025)

Fat-to-Thin Policy Optimization: Offline RL with Sparse Policies
di: Zhu, Lingwei, et al.
Pubblicazione: (2025)

Multi-scale Predictive Representations for Goal-conditioned Reinforcement Learning
di: Adaikkappan, Valliappan Chidambaram, et al.
Pubblicazione: (2026)

Are Expressive Models Truly Necessary for Offline RL?
di: Wang, Guan, et al.
Pubblicazione: (2024)

AdamO: A Collapse-Suppressed Optimizer for Offline RL
di: Qiao, Nan, et al.
Pubblicazione: (2026)

Augmenting Online RL with Offline Data is All You Need: A Unified Hybrid RL Algorithm Design and Analysis
di: Huang, Ruiquan, et al.
Pubblicazione: (2025)

An Empirical Study on the Effectiveness of Incorporating Offline RL As Online RL Subroutines
di: Su, Jianhai, et al.
Pubblicazione: (2025)

Less is More: Clustered Cross-Covariance Control for Offline RL
di: Qiao, Nan, et al.
Pubblicazione: (2026)

Dual Alignment Maximin Optimization for Offline Model-based RL
di: Zhou, Chi, et al.
Pubblicazione: (2025)

Improving Offline RL by Blending Heuristics
di: Geng, Sinong, et al.
Pubblicazione: (2023)