5 papers
Dual-Actor Fine-Tuning of VLA Models: A Talk-and-Tweak Human-in-the-Loop Approach
Piaopiao Jin, Qi Wang, Guokang Sun +3
Vision-language-action (VLA) models demonstrate strong generalization in robotic manipulation but face challenges in complex, real-world tasks. While supervised fine-tuning with de…
TGRPO :Fine-tuning Vision-Language-Action Model via Trajectory-wise Group Relative Policy Optimization
Zengjue Chen, Runliang Niu, He Kong +3
Visual-Language-Action (VLA) models have demonstrated strong cross-scenario generalization capabilities in various robotic tasks through large-scale pre-training and task-specific…
Strategy-Augmented Planning for Large Language Models via Opponent Exploitation
Shuai Xu, Sijia Cui, Yanna Wang +2
Efficiently modeling and exploiting opponents is a long-standing challenge in adversarial domains. Large Language Models (LLMs) trained on extensive textual data have recently demo…
ScreenExplorer: Training a Vision-Language Model for Diverse Exploration in Open GUI World
Runliang Niu, Jinglong Ji, Yi Chang +1
The rapid progress of large language models (LLMs) has sparked growing interest in building Artificial General Intelligence (AGI) within Graphical User Interface (GUI) environments…
CarPlanner: Consistent Auto-regressive Trajectory Planning for Large-scale Reinforcement Learning in Autonomous Driving
Dongkun Zhang, Jiaming Liang, Ke Guo +5
Trajectory planning is vital for autonomous driving, ensuring safe and efficient navigation in complex environments. While recent learning-based methods, particularly reinforcement…