5 papers
ProOPF: Benchmarking and Improving LLMs for Professional-Grade Power Systems Optimization Modeling
Chao Shen, Zihan Guo, Xu Wan +6
Growing renewable penetration introduces substantial uncertainty into power system operations, necessitating frequent adaptation of dispatch objectives and constraints and challeng…
LocationReasoner: Evaluating LLMs on Real-World Site Selection Reasoning
Miho Koda, Yu Zheng, Ruixian Ma +4
Recent advances in large language models (LLMs), particularly those enhanced through reinforced post-training, have demonstrated impressive reasoning capabilities, as exemplified b…
LLM-DMD: Large Language Model-based Power System Dynamic Model Discovery
Chao Shen, Zihan Guo, Ke Zuo +2
Current model structural discovery methods for power system dynamics impose rigid priors on the basis functions and variable sets of dynamic models while often neglecting algebraic…
Sophia: A Persistent Agent Framework of Artificial Life
Mingyang Sun, Feng Hong, Weinan Zhang
The development of LLMs has elevated AI agents from task-specific tools to long-lived, decision-making entities. Yet, most architectures remain static and reactive, tethered to man…
NeuroDeX: Unlocking Diverse Support in Decompiling Deep Neural Network Executables
Yilin Li, Guozhu Meng, Mingyang Sun +4
On-device deep learning models have extensive real world demands. Deep learning compilers efficiently compile models into executables for deployment on edge devices, but these exec…