Trajectory planning for autonomous driving requires both high-level reasoning and precise low-level control. Large Language Models (LLMs) offer semantic-rich planning capabilities, however, their application is limited by hallucinated reasoning, poor grounding in environment dynamics, and limited numerical precision in...
Zhihong Cui, Hengyu Liu, Zhang-Kai Wu et al.· 0 citations
This work presents GreenPipe, an automated profiling-training-validation pipeline that builds multi-resource regression models from external power meter measurements and attributes power to containers proportionally, exposing performance-energy trade-offs across workload configurations.
Meng-Xue Wang, Pei-Ni Liu, Amirhosein Taherkordi et al.· 0 citations
This work presents ongoing research on the frequency-scaling behavior of NVIDIA GPUs when executing ML/AI workloads. Our preliminary findings show that, on lower-performance GPUs, the operating frequency is strongly affected by the recent workload history-typically within an 80ms window. This behavior challenges a comm...
T. Le, Hoang-Loc La, Amirhosein Taherkordi et al.· 2026 IEEE 26th International...· 1 citation
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