"behavior cloning" Papers

13 papers found

Agent-Aware Training for Agent-Agnostic Action Advising in Deep Reinforcement Learning

Yaoquan Wei, Shunyu Liu, Jie Song et al.

AAAI 2025paperarXiv:2311.16807
1
citations

An Optimal Discriminator Weighted Imitation Perspective for Reinforcement Learning

Haoran Xu, Shuozhe Li, Harshit Sikchi et al.

ICLR 2025arXiv:2504.13368
3
citations

DPAIL: Training Diffusion Policy for Adversarial Imitation Learning without Policy Optimization

Yunseon Choi, Minchan Jeong, Soobin Um et al.

NEURIPS 2025

Incentivizing Reasoning for Advanced Instruction-Following of Large Language Models

Yulei Qin, Gang Li, Zongyi Li et al.

NEURIPS 2025arXiv:2506.01413
5
citations

Interactive and Hybrid Imitation Learning: Provably Beating Behavior Cloning

Yichen Li, Chicheng Zhang

NEURIPS 2025arXiv:2412.07057

Latent Policy Barrier: Learning Robust Visuomotor Policies by Staying In-Distribution

Zhanyi Sun, Shuran Song

NEURIPS 2025spotlightarXiv:2508.05941
7
citations

Predictive Inverse Dynamics Models are Scalable Learners for Robotic Manipulation

Yang Tian, Sizhe Yang, Jia Zeng et al.

ICLR 2025arXiv:2412.15109
93
citations

Robots Pre-train Robots: Manipulation-Centric Robotic Representation from Large-Scale Robot Datasets

Guangqi Jiang, Yifei Sun, Tao Huang et al.

ICLR 2025arXiv:2410.22325
26
citations

Self-Improvement for Neural Combinatorial Optimization: Sample Without Replacement, but Improvement

Dominik Grimm, Jonathan Pirnay

ICLR 2025arXiv:2403.15180
28
citations

Value-aligned Behavior Cloning for Offline Reinforcement Learning via Bi-level Optimization

Xingyu Jiang, Ning Gao, Xiuhui Zhang et al.

ICLR 2025

Videos are Sample-Efficient Supervisions: Behavior Cloning from Videos via Latent Representations

Xin Liu, Haoran Li, Dongbin Zhao

NEURIPS 2025arXiv:2512.21586

How to Leverage Diverse Demonstrations in Offline Imitation Learning

Sheng Yue, Jiani Liu, Xingyuan Hua et al.

ICML 2024arXiv:2405.17476
7
citations

PRISE: LLM-Style Sequence Compression for Learning Temporal Action Abstractions in Control

Ruijie Zheng, Ching-An Cheng, Hal Daumé et al.

ICML 2024oralarXiv:2402.10450
16
citations