2 citations · 2 across the 6 of their papers we have counts for
6 papers
VLA-Scope: Shift-Aware Failure Prediction for Vision-Language-Action Models
Kaiwen Zhu, Dongfang Liu, Liangkai Liu
Vision-language-action (VLA) models map visual observations and natural-language instructions to robotic actions, but distribution shifts can compromise their reliability. Because…
Context-Aware Intelligent Vehicles
Liangkai Liu, Shuyao Shi, Mingke Wang +4
Intelligent vehicles increasingly support adaptive applications beyond driving themselves, ranging from context-aware ADAS and automated driving to in-cabin monitoring and fleet ma…
Adversarial Calibration Attack on Autonomous Vehicles
Liangkai Liu, Qingzhao Zhang, Kang G. Shin
Autonomous vehicles (AVs) rely on accurate camera-LiDAR calibration for multimodal sensor fusion. In practice, calibration can drift due to vibration, temperature variation, or min…
MM-BEV: Enhancing Timeliness by Computing Where and When it Matters
Liangkai Liu, Kang G. Shin
Multimodal bird's-eye-view (BEV) perception combines LiDAR depth accuracy with dense camera semantics, but its high computational cost and imperfect sensing conditions make real-ti…
Lotus: learning-based online thermal and latency variation management for two-stage detectors on edge devices
Yifan Gong, Yushu Wu, Zheng Zhan +5
Two-stage object detectors exhibit high accuracy and precise localization, especially for identifying small objects that are favorable for various edge applications. However, the h…
Achieving the Safety and Security of the End-to-End AV Pipeline
Noah T. Curran, Minkyoung Cho, Ryan Feng +6
In the current landscape of autonomous vehicle (AV) safety and security research, there are multiple isolated problems being tackled by the community at large. Due to the lack of c…