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Found 4 papers, 2 papers with code
Measuring Distributional Shifts in Text: The Advantage of Language Model-Based Embeddings
Then we study the effectiveness of our approach when applied to text embeddings generated by both LLMs and classical embedding algorithms.
Auditing Black-Box Prediction Models for Data Minimization Compliance
In this paper, we focus on auditing black-box prediction models for compliance with the GDPR’s data minimization principle.
Fair Inputs and Fair Outputs: The Incompatibility of Fairness in Privacy and Accuracy
We show that for an optimal classifier these three properties are in general incompatible, and we explain what common properties of data make them incompatible.
Fighting Fire with Fire: Using Antidote Data to Improve Polarization and Fairness of Recommender Systems
We take as our model system the matrix factorization approach to recommendation, and we propose a set of measures to capture the polarization or fairness of recommendations.
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