Benchmarking Tool
Benchmarking tools are software platforms designed to systematically evaluate the performance and characteristics of machine learning models, particularly in complex domains like robotics and autonomous systems. Current research emphasizes the need for comprehensive tools that assess not only model accuracy ("utility") but also fairness, explainability, and cost-effectiveness, often incorporating diverse metrics and standardized reporting. These tools are crucial for advancing the field by enabling reproducible research, facilitating fair comparisons between different models and algorithms, and ultimately driving the development of more robust and reliable AI systems for real-world applications.
Papers
CEBench: A Benchmarking Toolkit for the Cost-Effectiveness of LLM Pipelines
Wenbo Sun, Jiaqi Wang, Qiming Guo, Ziyu Li, Wenlu Wang, Rihan Hai
FairX: A comprehensive benchmarking tool for model analysis using fairness, utility, and explainability
Md Fahim Sikder, Resmi Ramachandranpillai, Daniel de Leng, Fredrik Heintz