activity
20232026
most citedEvaluation Measures of Individual Item Fairness for Recommender Systems: A Critical Study

34 citations · 43 across the 9 of their papers we have counts for

collaborators

10 papers

cs.CL2026

Last Translation Benchmark

Vilém Zouhar, Niyati Bafna, Mukund Choudhary +241

For scientific progress, we need benchmarks that test the limits of state-of-the-art models, and evaluation methods that inform us about failure cases. As models get stronger, stan…

cs.IR2026

LegalPincite: Multi-level Legal Information Retrieval Dataset

Theresia Veronika Rampisela, Henrik Palmer Olsen, Giovanni Colavizza

A common task in legal Information Retrieval (IR) is to find relevant legal sources from case-law collections. While legal practice often requires pinpoint citations (pincites) to…

cs.IR2026

Offline Evaluation Measures of Fairness in Recommender Systems

Theresia Veronika Rampisela

The evaluation of recommender system fairness has become increasingly important, especially with recent legislation that emphasises the development of fair and responsible artifici…

cs.IR2026

Can Fairness Be Prompted? Prompt-Based Debiasing Strategies in High-Stakes Recommendations

Mihaela Rotar, Theresia Veronika Rampisela, Maria Maistro

Large Language Models (LLMs) can infer sensitive attributes such as gender or age from indirect cues like names and pronouns, potentially biasing recommendations. While several deb…

cs.CY2026

Measuring Individual User Fairness with User Similarity and Effectiveness Disparity

Theresia Veronika Rampisela, Maria Maistro, Tuukka Ruotsalo +1

Individual user fairness is commonly understood as treating similar users similarly. In Recommender Systems (RSs), several evaluation measures exist for quantifying individual user…

cs.CY2025

The Quest for Reliable Metrics of Responsible AI

Theresia Veronika Rampisela, Maria Maistro, Tuukka Ruotsalo +1

The development of Artificial Intelligence (AI), including AI in Science (AIS), should be done following the principles of responsible AI. Progress in responsible AI is often quant…