:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Lei, Xing, Zhang, Xuetao, Zhuang, Zifeng, Wang, Donglin
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2410.06648
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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

QHyer: Q-conditioned Hybrid Attention-mamba Transformer for Offline Goal-conditioned RL
by: Lei, Xing, et al.
Published: (2026)

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

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

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

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

Imitating from auxiliary imperfect demonstrations via Adversarial Density Weighted Regression
by: Zhang, Ziqi, et al.
Published: (2024)

Context-Former: Stitching via Latent Conditioned Sequence Modeling
by: Zhang, Ziqi, et al.
Published: (2024)

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

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

Boundary-to-Region Supervision for Offline Safe Reinforcement Learning
by: Su, Huikang, et al.
Published: (2025)

VARD: Efficient and Dense Fine-Tuning for Diffusion Models with Value-based RL
by: Dai, Fengyuan, et al.
Published: (2025)

A dynamical clipping approach with task feedback for Proximal Policy Optimization
by: Zhang, Ziqi, et al.
Published: (2023)

On-Policy RL Meets Off-Policy Experts: Harmonizing Supervised Fine-Tuning and Reinforcement Learning via Dynamic Weighting
by: Zhang, Wenhao, et al.
Published: (2025)

TDMPBC: Self-Imitative Reinforcement Learning for Humanoid Robot Control
by: Zhuang, Zifeng, et al.
Published: (2025)

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

Unifying Goal-Conditioned RL and Unsupervised Skill Learning via Control-Maximization
by: Modirshanechi, Alireza, et al.
Published: (2026)

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

Accelerating Goal-Conditioned RL Algorithms and Research
by: Bortkiewicz, Michał, et al.
Published: (2024)

Goal-Conditioned Supervised Learning for LLM Fine-Tuning
by: Li, Shijun, et al.
Published: (2026)

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

TLDR: Unsupervised Goal-Conditioned RL via Temporal Distance-Aware Representations
by: Bae, Junik, et al.
Published: (2024)

Goal-Conditioned Supervised Learning for Multi-Objective Recommendation
by: Li, Shijun, et al.
Published: (2024)

World-Value-Action Model: Implicit Planning for Vision-Language-Action Systems
by: Li, Runze, et al.
Published: (2026)

Autonomous Learning From Success and Failure: Goal-Conditioned Supervised Learning with Negative Feedback
by: Zhang, Zeqiang, et al.
Published: (2025)

Adaptive $Q$-Aid for Conditional Supervised Learning in Offline Reinforcement Learning
by: Kim, Jeonghye, et al.
Published: (2024)

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

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

Functional Graphs for Predicting and Explaining Goal Failure in Sparse Goal-Conditioned RL
by: Dash, Shalley
Published: (2026)

Goal Exploration via Adaptive Skill Distribution for Goal-Conditioned Reinforcement Learning
by: Wu, Lisheng, et al.
Published: (2024)

Incorporating Spatial Information into Goal-Conditioned Hierarchical Reinforcement Learning via Graph Representations
by: Zhang, Shuyuan, et al.
Published: (2025)

Frozen Policy Iteration: Computationally Efficient RL under Linear $Q^π$ Realizability for Deterministic Dynamics
by: Ke, Yijing, et al.
Published: (2026)

1000 Layer Networks for Self-Supervised RL: Scaling Depth Can Enable New Goal-Reaching Capabilities
by: Wang, Kevin, et al.
Published: (2025)

Learning Optimal Individualized Decision Rules with Conditional Demographic Parity
by: Cui, Wenhai, et al.
Published: (2026)

Logic Synthesis Optimization with Predictive Self-Supervision via Causal Transformers
by: Karimi, Raika, et al.
Published: (2024)

Revisiting Weight Regularization for Low-Rank Continual Learning
by: Zheng, Yaoyue, et al.
Published: (2026)

Return-to-Go Is More Than a Number: Q-Guided Alignment for Return-Conditioned Supervised Learning
by: Yang, Yuxiao, et al.
Published: (2026)

SynRL: Aligning Synthetic Clinical Trial Data with Human-preferred Clinical Endpoints Using Reinforcement Learning
by: Das, Trisha, et al.
Published: (2024)

HMM for Discovering Decision-Making Dynamics Using Reinforcement Learning Experiments
by: Guo, Xingche, et al.
Published: (2024)

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