7 papers
Beyond Local Code Optimization: Multi-Agent Reasoning for Software System Optimization
Huiyun Peng, Parth Vinod Patil, Antonio Zhong Qiu +2
Large language models and AI agents have recently shown promise in automating software performance optimization, but existing approaches predominantly rely on local, syntax-driven…
How Do Agents Perform Code Optimization? An Empirical Study
Huiyun Peng, Antonio Zhong, Ricardo Andrés Calvo Méndez +2
Performance optimization is a critical yet challenging aspect of software development, often requiring a deep understanding of system behavior, algorithmic tradeoffs, and careful c…
AgentHub: A Registry for Discoverable, Verifiable, and Reproducible AI Agents
Erik Pautsch, Tanmay Singla, Parv Kumar +6
LLM-based agents are rapidly proliferating, yet the infrastructure for discovering, evaluating, and governing them remains fragmented compared to mature ecosystems like software pa…
A Guide to Stakeholder Analysis for Cybersecurity Researchers
James C Davis, Sophie Chen, Huiyun Peng +2
Stakeholder-based ethics analysis is now a formal requirement for submissions to top cybersecurity research venues. This requirement reflects a growing consensus that cybersecurity…
Recommending Pre-Trained Models for IoT Devices
Parth V. Patil, Wenxin Jiang, Huiyun Peng +7
The availability of pre-trained models (PTMs) has enabled faster deployment of machine learning across applications by reducing the need for extensive training. Techniques like qua…
Can Large-Language Models Help us Better Understand and Teach the Development of Energy-Efficient Software?
Ryan Hasler, Konstantin Läufer, George K. Thiruvathukal +5
Computing systems are consuming an increasing and unsustainable fraction of society's energy footprint, notably in data centers. Meanwhile, energy-efficient software engineering te…