46 citations · 47 across the 16 of their papers we have counts for
5 papers · 1 filter
Diffuse to Detect: Generative Diffusion Models for Unsupervised IC Anomaly Detection
Yuxuan Yin, Chen He, Todd Jacobs +4
Latent defect screening is challenged by extremely low failure rates, high-dimensional test data, and absence of labeled anomalies. We propose the first unsupervised anomaly detect…
LASER: Language Model Regression for Semi-Structured Workflow Resource and Runtime Estimation
Yuxuan Yin, Shengke Zhou, Yunjie Zhang +3
Accurate prediction of resource consumption and runtime for cloud workflow jobs is critical for scheduling efficiency, yet remains challenging due to the semi-structured nature of…
Transfer Learning for Minimum Operating Voltage Prediction in Advanced Technology Nodes: Leveraging Legacy Data and Silicon Odometer Sensing
Yuxuan Yin, Rebecca Chen, Boxun Xu +2
Accurate prediction of chip performance is critical for ensuring energy efficiency and reliability in semiconductor manufacturing. However, developing minimum operating voltage ($V…
Khan-GCL: Kolmogorov-Arnold Network Based Graph Contrastive Learning with Hard Negatives
Zihu Wang, Boxun Xu, Hejia Geng +1
Graph contrastive learning (GCL) has demonstrated great promise for learning generalizable graph representations from unlabeled data. However, conventional GCL approaches face two…
ADO-LLM: Analog Design Bayesian Optimization with In-Context Learning of Large Language Models
Yuxuan Yin, Yu Wang, Boxun Xu +1
Analog circuit design requires substantial human expertise and involvement, which is a significant roadblock to design productivity. Bayesian Optimization (BO), a popular machine l…