3 papers
eess.SP2026
Flow-PIN: A Two-Stage Power-Flow-Guided Method for System-Wide Multivariate Profile Inpainting in Distribution Networks
Zhenghao Zhou, Yiyan Li, Yike Guo +3
High-quality system measurement data is critical for power distribution system operation. As deep generative models (e.g., GAN, Diffusion, etc.) have been widely studied to solve t…
eess.SY2026
A Physics-guided Fine-tuned LLM-based Framework for Customized Power Distribution System Feeder Generation
Zhenghao Zhou, Yiyan Li, Tao Xu +3
Power distribution system feeder models (e.g., IEEE 33-bus system, IEEE 13-bus system, etc.) are cornerstones for conducting power distribution system studies. As real-world feeder…
cs.LG2026
Sparse Adapter Fusion for Continual Learning in NLP
Min Zeng, Xi Chen, Haiqin Yang +1
Continual learning in natural language processing plays a crucial role in adapting to evolving data and preventing catastrophic forgetting. Despite significant progress, existing m…