Elo Rating

The Elo rating system, initially designed for chess, quantifies skill levels in competitive scenarios by comparing players' performance in head-to-head matchups. Current research focuses on improving Elo's robustness and applicability beyond its traditional uses, including evaluating large language models and adapting it for non-transitive games through techniques like graph embeddings and multi-dimensional extensions. These advancements aim to enhance the accuracy and efficiency of skill assessment across diverse domains, impacting fields like AI evaluation and competitive game analysis. Concerns remain regarding the system's inherent limitations, particularly its sensitivity to hyperparameters and potential biases in human or AI-based evaluations.