2 citations · 3 across the 5 of their papers we have counts for
7 papers
Configuring RAG Systems: What Breaks, Where Originates, and How to Fix
Liangyu Chen, Youpeng Ma, Yulong Ye +2
Retrieval-Augmented Generation (RAG) has emerged as a dominant paradigm for improving Large Language Model (LLM) by intertwining it with other components, such as a vector/graph da…
When to Use Which? Benchmarking Optimisers for Configurable Systems under Varying Budgets
Chao Jiang, Yulong Ye, Tao Chen +1
Software configuration tuning is crucial for optimising system performance, and various optimisers have emerged over the last decade. Yet, the time required during the tuning proce…
LLMSYS-HPOBench: Hyperparameter Optimization Benchmark Suite for Real-World LLM Systems
Siyu Wu, Yulong Ye, Zezhen Xiang +3
Large Language Model (LLM) systems have been the frontier of AI in many application domains, leading to new challenges and opportunities for hyperparameter optimization (HPO) for t…
Revealing Domain-Spatiality Patterns for Configuration Tuning: Domain Knowledge Meets Fitness Landscapes
Yulong Ye, Hongyuan Liang, Chao Jiang +2
Configuration tuning for better performance is crucial in quality assurance. Yet, there has long been a mystery on tuners' effectiveness, due to the black-box nature of configurabl…
MOOT: a Repository of Many Multi-Objective Optimization Tasks
Tim Menzies, Tao Chen, Yulong Ye +4
Software engineers must make decisions that trade off competing goals (faster vs. cheaper, secure vs. usable, accurate vs. interpretable, etc.). Despite MSR's proven techniques for…
Distilled Lifelong Self-Adaptation for Configurable Systems
Yulong Ye, Tao Chen, Miqing Li
Modern configurable systems provide tremendous opportunities for engineering future intelligent software systems. A key difficulty thereof is how to effectively self-adapt the conf…
GreenStableYolo: Optimizing Inference Time and Image Quality of Text-to-Image Generation
Jingzhi Gong, Sisi Li, Giordano d'Aloisio +4
Tuning the parameters and prompts for improving AI-based text-to-image generation has remained a substantial yet unaddressed challenge. Hence we introduce GreenStableYolo, which im…