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The Bradley-Terry-Luce (BTL) model is a benchmark model for pairwise comparisons between individuals. Despite recent progress on the first-order asymptotics of several popular procedures, the understanding of uncertainty quantification in…

Statistics Theory · Mathematics 2022-08-11 Chao Gao , Yandi Shen , Anderson Y. Zhang

With the advent of highly capable instruction-tuned neural language models, benchmarking in natural language processing (NLP) is increasingly shifting towards pairwise comparison leaderboards, such as LMSYS Arena, from traditional global…

Computation and Language · Computer Science 2025-09-24 Georgii Levtsov , Dmitry Ustalov

Comparing alternatives in pairs is a well-known method of ranking creation. Experts are asked to perform a series of binary comparisons and then, using mathematical methods, the final ranking is prepared. As experts conduct the individual…

Discrete Mathematics · Computer Science 2018-12-12 Konrad Kułakowski

Pairwise comparison matrices are increasingly used in settings where some pairs are missing. However, there exist few inconsistency indices for similar incomplete data sets and no reasonable measure has an associated threshold. This paper…

Statistics Theory · Mathematics 2022-02-03 Kolos Csaba Ágoston , László Csató

In this work, we develop a hypothesis testing framework to determine whether pairwise comparison data is generated by an underlying \emph{generalized Thurstone model} $\mathcal{T}_F$ for a given choice function $F$. While prior work has…

Machine Learning · Computer Science 2025-12-03 Anuran Makur , Japneet Singh

Many applications, e.g. in content recommendation, sports, or recruitment, leverage the comparisons of alternatives to score those alternatives. The classical Bradley-Terry model and its variants have been widely used to do so. The…

Methodology · Statistics 2024-02-23 Julien Fageot , Sadegh Farhadkhani , Lê Nguyên Hoang , Oscar Villemaud

The question of aggregating pair-wise comparisons to obtain a global ranking over a collection of objects has been of interest for a very long time: be it ranking of online gamers (e.g. MSR's TrueSkill system) and chess players, aggregating…

Machine Learning · Computer Science 2015-11-13 Sahand Negahban , Sewoong Oh , Devavrat Shah

We consider the problem of ranking a set of items from pairwise comparisons in the presence of features associated with the items. Recent works have established that $O(n\log(n))$ samples are needed to rank well when there is no feature…

Machine Learning · Computer Science 2021-02-10 Aadirupa Saha , Arun Rajkumar

We revisit the problem of inferring the overall ranking among entities in the framework of Bradley-Terry-Luce (BTL) model, based on available empirical data on pairwise preferences. By a simple transformation, we can cast the problem as…

Machine Learning · Computer Science 2016-05-10 Vivek S. Borkar , Nikhil Karamchandani , Sharad Mirani

Many applications such as recommendation systems or sports tournaments involve pairwise comparisons within a collection of $n$ items, the goal being to aggregate the binary outcomes of the comparisons in order to recover the latent strength…

Statistics Theory · Mathematics 2023-07-13 Eglantine Karlé , Hemant Tyagi

Incomplete pairwise comparison matrices offer a natural way of expressing preferences in decision making processes. Although ordinal information is crucial, there is a bias in the literature: cardinal models dominate. Ordinal models usually…

Optimization and Control · Mathematics 2020-12-15 Luca Faramondi , Gabriele Oliva , Sándor Bozóki

The rating of items based on pairwise comparisons has been a topic of statistical investigation for many decades. Numerous approaches have been proposed. One of the best known is the Bradley-Terry model. This paper seeks to assemble and…

Statistics Theory · Mathematics 2025-08-08 Ian Hamilton , Nick Tawn , David Firth

We study the ranking of individuals, teams, or objects, based on pairwise comparisons between them, using the Bradley-Terry model. Estimates of rankings within this model are commonly made using a simple iterative algorithm first introduced…

Machine Learning · Statistics 2023-08-16 M. E. J. Newman

This paper explores the preference-based top-$K$ rank aggregation problem. Suppose that a collection of items is repeatedly compared in pairs, and one wishes to recover a consistent ordering that emphasizes the top-$K$ ranked items, based…

Machine Learning · Computer Science 2015-05-29 Yuxin Chen , Changho Suh

Comparative Judgement is an assessment method where item ratings are estimated based on rankings of subsets of the items. These rankings are typically pairwise, with ratings taken to be the estimated parameters from fitting a Bradley-Terry…

Methodology · Statistics 2024-05-22 Ian Hamilton , Nick Tawn

Paired comparison models, such as Bradley-Terry and Thurstone-Mosteller, are commonly used to estimate relative strengths of pairwise compared items in tournament-style data. We discuss estimation of paired comparison models with a ridge…

Methodology · Statistics 2024-10-03 Cristiano Varin , David Firth

This paper considers ranking inference of $n$ items based on the observed data on the top choice among $M$ randomly selected items at each trial. This is a useful modification of the Plackett-Luce model for $M$-way ranking with only the top…

Methodology · Statistics 2023-01-09 Jianqing Fan , Zhipeng Lou , Weichen Wang , Mengxin Yu

We consider data in the form of pairwise comparisons of n items, with the goal of precisely identifying the top k items for some value of k < n, or alternatively, recovering a ranking of all the items. We analyze the Copeland counting…

Machine Learning · Computer Science 2016-04-28 Nihar B. Shah , Martin J. Wainwright

The Bradley-Terry model is widely used for pairwise comparison data analysis. In this paper, we analyze the asymptotic behavior of the maximum likelihood estimator of the Bradley-Terry model in its logistic parameterization, under a general…

Statistics Theory · Mathematics 2022-05-10 Weichen Wu , Brian W. Junker , Nynke M. D. Niezink

In this work, we leverage a generative data model considering comparison noise to develop a fast, precise, and informative ranking algorithm from pairwise comparisons that produces a measure of confidence on each comparison. The problem of…

Machine Learning · Computer Science 2025-07-24 Filipa Valdeira , Cláudia Soares