10 papers
Counterfactual Neighborhood Risk Fields: Evidence-Grounded Selective Safety for Vision-Language Models
Tianshi Wang, Jingsong Wang, Fengling Li +3
Representation-based safety defenses for vision-language models (VLMs) often learn to separate harmful from benign inputs, but separation alone does not establish what a risk score…
UniTexture: Cross-Task Universal Adversarial Textures for Vision-Language-Action Models
Yukun Dai, Mingzhe Dai, Tianshi Wang +3
Vision-Language-Action (VLA) models have emerged as generalist robotic policies capable of following diverse language instructions and performing a wide range of manipulation tasks…
ActFovea: Runtime Safeguarding for VLA Policies via Spatiotemporal Visual-Action Consistency
Wenda Yu, Tianshi Wang, Fengling Li +3
Vision-language-action (VLA) policies achieve strong performance in robotic manipulation but remain vulnerable to runtime disturbances that break the temporal alignment among visua…
DA-PTQ: Drift-Aware Post-Training Quantization for Efficient Vision-Language-Action Models
Siyuan Xu, Tianshi Wang, Fengling Li +2
Vision-Language-Action models (VLAs) have demonstrated strong potential for embodied AI, yet their deployment on resource-limited robots remains challenging due to high memory and…
Non-Markovian Long-Horizon Robot Manipulation via Keyframe Chaining
Yipeng Chen, Wentao Tan, Lei Zhu +4
Existing Vision-Language-Action (VLA) models often struggle to generalize to long-horizon tasks due to their heavy reliance on immediate observations. While recent studies incorpor…
MOTIF: Learning Action Motifs for Few-shot Cross-Embodiment Transfer
Heng Zhi, Wentao Tan, Lei Zhu +4
While vision-language-action (VLA) models have advanced generalist robotic learning, cross-embodiment transfer remains challenging due to kinematic heterogeneity and the high cost…
AC^2-VLA: Action-Context-Aware Adaptive Computation in Vision-Language-Action Models for Efficient Robotic Manipulation
Wenda Yu, Tianshi Wang, Fengling Li +2
Vision-Language-Action (VLA) models have demonstrated strong performance in robotic manipulation, yet their closed-loop deployment is hindered by the high latency and compute cost…
A Step Toward World Models: A Survey on Robotic Manipulation
Peng-Fei Zhang, Ying Cheng, Xiaofan Sun +4
Autonomous agents are increasingly expected to operate in complex, dynamic, and uncertain environments, performing tasks such as manipulation, navigation, and decision-making. Achi…
ActDistill: General Action-Guided Self-Derived Distillation for Efficient Vision-Language-Action Models
Wencheng Ye, Tianshi Wang, Lei Zhu +3
Recent Vision-Language-Action (VLA) models have shown impressive flexibility and generalization, yet their deployment in robotic manipulation remains limited by heavy computational…
Reason Like a Radiologist: Chain-of-Thought and Reinforcement Learning for Verifiable Report Generation
Peiyuan Jing, Kinhei Lee, Zhenxuan Zhang +7
Radiology report generation is critical for efficiency but current models lack the structured reasoning of experts, hindering clinical trust and explainability by failing to link v…