Recent advances in the Bradley--Terry Model: theory, algorithms, and applications
Methodology
2026-01-23 v2
Abstract
This article surveys recent progress in the Bradley-Terry (BT) model and its extensions. We focus on the statistical and computational aspects, with emphasis on the regime in which both the number of objects and the volume of comparisons tend to infinity, a setting relevant to large-scale applications. The main topics include asymptotic theory for statistical estimation and inference, along with the associated algorithms. We also discuss applications of these models, including recent work on preference alignment in machine learning. Finally, we discuss several key challenges and outline directions for future research.
Cite
@article{arxiv.2601.14727,
title = {Recent advances in the Bradley--Terry Model: theory, algorithms, and applications},
author = {Shuxing Fang and Ruijian Han and Yuanhang Luo and Yiming Xu},
journal= {arXiv preprint arXiv:2601.14727},
year = {2026}
}