3 papers
cs.AR2026
BigPower: Hierarchical Source-Level Module Power Estimation for CPUs with Large Language Models
Honghua Zhu, Chunjie Luo, Jianfeng Zhan
Accurate power estimation is important for understanding and optimizing CPU power behavior, yet practical workflows often rely on simulation-derived information or post-silicon ana…
cs.LG2025
KAIROS: Unified Training for Universal Non-Autoregressive Time Series Forecasting
Kuiye Ding, Fanda Fan, Zheya Wang +5
In the World Wide Web, reliable time series forecasts provide the forward-looking signals that drive resource planning, cache placement, and anomaly response, enabling platforms to…
cs.AI2025
DualSG: A Dual-Stream Explicit Semantic-Guided Multivariate Time Series Forecasting Framework
Kuiye Ding, Fanda Fan, Yao Wang +6
Multivariate Time Series Forecasting plays a key role in many applications. Recent works have explored using Large Language Models for MTSF to take advantage of their reasoning abi…