6 papers
Shortcut Learning in Legal Judgment Prediction: Empirical Evidence from the UK Employment Tribunal
Joe Watson, Joana Ribeiro de Faria, Marcus Tomalin +6
Current Legal Judgment Prediction (LJP) is constrained by its reliance on post-hoc judicial materials, increasing the likelihood that models perform retrospective classification ra…
Uncertainty in Bayesian Leave-One-Out Cross-Validation Based Model Comparison
Tuomas Sivula, MÃ¥ns Magnusson, Asael Alonzo Matamoros +1
It is useful to estimate the expected predictive performance of models planned to be used for prediction. We focus on leave-one-out cross-validation (LOO-CV), which has become a po…
Iterative Data Curation with Theoretical Guarantees
Väinö Yrjänäinen, Johan Jonasson, Måns Magnusson
In recent years, more and more large data sets have become available. Data accuracy, the absence of verifiable errors in data, is crucial for these large materials to enable high-q…
Prediction-powered estimators for finite population statistics in highly imbalanced textual data: Public hate crime estimation
Hannes Waldetoft, Jakob Torgander, MÃ¥ns Magnusson
Estimating population parameters in finite populations of text documents can be challenging when obtaining the labels for the target variable requires manual annotation. To address…
An Image is Worth Topics: A Visual Structural Topic Model with Pretrained Image Embeddings
MatÃas Piqueras, Alexandra Segerberg, Matteo Magnani +2
Political scientists are increasingly interested in analyzing visual content at scale. However, the existing computational toolbox is still in need of methods and models attuned to…
Frequentist Oracle Properties of Bayesian Stacking Estimators
Valentin Zulj, Shaobo Jin, MÃ¥ns Magnusson
Compromise estimation entails using a weighted average of outputs from several candidate models, and is a viable alternative to model selection when the choice of model is not obvi…