1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.SE2026
Can Adjusting Hyperparameters Lead to Green Deep Learning: An Empirical Study on Correlations between Hyperparameters and Energy Consumption of Deep Learning Models
Taoran Wang, Yanhui Li, Mingliang Ma +2
Context: Along with developing Deep learning (DL) models, larger datasets and more complex model structures are applied, leading to rising computing resources and energy consumptio…
cs.SE2025
WITNESS: A lightweight and practical approach to fine-grained predictive mutation testing
Zeyu Lu, Peng Zhang, Chun Yong Chong +5
Existing fine-grained predictive mutation testing studies predominantly rely on deep learning, which faces two critical limitations in practice: (1) Exorbitant computational costs.…
cs.SE2024★ 1 cited
A Roadmap on Modern Code Review: Challenges and Opportunities
Zezhou Yang, Cuiyun Gao, Zhaoqiang Guo +4
Over the past decade, modern code review (MCR) has been established as a cornerstone of software quality assurance and a vital channel for knowledge transfer within development tea…