13 citations · 21 across the 8 of their papers we have counts for
8 papers
VLA-Precision: Asymmetric Co-Bootstrapping for Efficient Real-World Online RL of Vision-Language-Action Models
Chenyu Su, Zhaolong Shen, Yuan Qian +8
Pretrained vision-language-action (VLA) models enable broad manipulation but remain unreliable in tasks demanding precision and repeatability. Applying real-world online reinforcem…
VINE: Taming Generative Control Policies for Reinforcement Learning
Rushuai Yang, Zhuo Han, Houlin Li +10
Flow-matching policies have emerged as an effective policy parameterization for robot learning. They iteratively generate actions from noise, enabling highly expressive modeling of…
A GPU-Parallel Framework for Heterogeneous Multi-Task Reinforcement Learning
Rui Zhang, Qiwei Wu, Zhengyu Zhang +7
GPU-parallel simulation provides abundant robot interaction, but existing benchmarks rarely combine this scale with heterogeneous manipulation tasks and standardized multi-task RL…
Q-VGM: Q-Guided Value-Gradient Matching for Offline-to-Online RL of Flow-Matching VLA Policies
Ziqian Wang, Rui Zhang, Yitian Liu +3
We propose Q-Guided Value-Gradient Matching (Q-VGM), an offline-to-online RL method for fine-tuning flow-matching vision-language-action policies with a learned critic. Directly ap…
CARE-RL: Capability-Aware Reinforcement Learning for Mitigating Cross-Domain Conflicts
Rui Zhang, Xinle Wu, Yao Lu
Reinforcement learning (RL) with verifiable rewards has achieved strong progress in reasoning-oriented LLMs, but extending it to multi-domain RL remains challenging due to reward u…
LithoGRPO: Fast Inverse Lithography via GRPO Reinforced Flow Matching
Yao Lai, Xuyuan Xiong, Zeyue Xue +7
In semiconductor manufacturing, lithography projects circuit layouts onto silicon wafers through an optical mask. As circuit features shrink below the wavelength of light, optical…
CaloChallenge 2022: A Community Challenge for Fast Calorimeter Simulation
Claudius Krause, Michele Faucci Giannelli, Gregor Kasieczka +66
We present the results of the "Fast Calorimeter Simulation Challenge 2022" - the CaloChallenge. We study state-of-the-art generative models on four calorimeter shower datasets of i…
CaloShowerGAN, a Generative Adversarial Networks model for fast calorimeter shower simulation
Michele Faucci Giannelli, Rui Zhang
In particle physics, the demand for rapid and precise simulations is rising. The shift from traditional methods to machine learning-based approaches has led to significant advancem…