Related papers: Predicting Brazilian court decisions
Fractional scoring has been proposed to avoid inconsistencies in the attribution of publications to percentile rank classes. Uncertainties and ambiguities in the evaluation of percentile ranks can be demonstrated most easily with small…
Context: Software code review aims to early find code anomalies and to perform code improvements when they are less expensive. However, issues and challenges faced by developers who do not apply code review practices regularly are unclear.…
Being able to predict when invoices will be paid is valuable in multiple industries and supports decision-making processes in most financial workflows. However, due to the complexity of data related to invoices and the fact that the…
The analysis of data such as graphs has been gaining increasing attention in the past years. This is justified by the numerous applications in which they appear. Several methods are present to predict graphs, but much fewer to quantify the…
An open problem posed by the first author is the complexity to decide whether a sequence of nonnegative integer numbers can be the final score of a football tournament. In this paper we propose polynomial time approximate and exponential…
Evaluating Large Language Models (LLMs) in open-ended scenarios is challenging because existing benchmarks and metrics can not measure them comprehensively. To address this problem, we propose to fine-tune LLMs as scalable judges (JudgeLM)…
The FIFA Men's World Cup Tournament (WCT) is the most important football (soccer) competition, attracting worldwide attention. A popular practice among football fans in Brazil is to organize contests in which each participant informs…
Brazilian Portuguese and European Portuguese are two varieties of the same language and, despite their close similarities, they exhibit several differences. However, there is a significant disproportion in the availability of resources…
This note proves a law of large numbers for predicting several steps ahead, which, in the case of uniformly bounded random variables, generalizes the standard law of large numbers for martingales; the standard law of large numbers…
The Brazilian commercial aviation system achieved the first position among Latin American countries and the fifteenth place worldwide on the Revenue Passenger-Kilometer (RPK) ranking. The availability of data regarding flight, including…
In this work, we study the behavior of Brazilian politicians and political parties with the help of clustering algorithms for signed social networks. For this purpose, we extract and analyze a collection of signed networks representing…
This paper presents some useful mathematical results involved in football table prediction. In addition, some empirical results indicate that an alternative methodology for football table prediction may produce high quality forecasts with…
Prediction is critical for decision-making under uncertainty and lends validity to statistical inference. With targeted prediction, the goal is to optimize predictions for specific decision tasks of interest, which we represent via…
Legal Judgment Prediction (LJP) aims to predict the outcomes of legal cases based on factual descriptions, serving as a fundamental task to advance the development of legal systems. Traditional methods often rely on statistical analyses or…
Legal information retrieval in Portuguese remains difficult to evaluate systematically because available datasets differ widely in document type, query style, and relevance definition. We present JU\'A, a public benchmark for Brazilian…
The paper considers the problem of multi-objective decision support when outcomes are uncertain. We extend the concept of Pareto-efficient decisions to take into account the uncertainty of decision outcomes across varying contexts. This…
This paper presents the first dataset for Japanese Legal Judgment Prediction (LJP), the Japanese Tort-case Dataset (JTD), which features two tasks: tort prediction and its rationale extraction. The rationale extraction task identifies the…
E-Commerce marketplaces support millions of daily transactions, and some disagreements between buyers and sellers are unavoidable. Resolving disputes in an accurate, fast, and fair manner is of great importance for maintaining a trustworthy…
This study describes the experimental application of Machine Learning techniques to build prediction models that can assess the injury risk associated with traffic accidents. This work uses an freely available data set of traffic accident…
The measurement of the efficiency of an event selection is always an important part of the analysis of experimental data. The statistical techniques which are needed to determine the efficiency and its uncertainty are reviewed. Frequentist…