Search Results for author:
Found 5 papers, 3 papers with code
Weakly Supervised Detection of Hallucinations in LLM Activations
We introduce a weakly supervised auditing technique using a subset scanning approach to detect anomalous patterns in LLM activations from pre-trained models.
Designing Long-term Group Fair Policies in Dynamical Systems
Neglecting the effect that decisions have on individuals (and thus, on the underlying data distribution) when designing algorithmic decision-making policies may increase inequalities and unfairness in the long term - even if fairness considerations were taken in the policy design process.
Don't Throw it Away! The Utility of Unlabeled Data in Fair Decision Making
In addition, data is often selectively labeled, i. e., even the biased labels are only observed for a small fraction of the data that received a positive decision.
VACA: Design of Variational Graph Autoencoders for Interventional and Counterfactual Queries
In this paper, we introduce VACA, a novel class of variational graph autoencoders for causal inference in the absence of hidden confounders, when only observational data and the causal graph are available.
Variational Causal Autoencoder for Interventional and Counterfactual Queries
We propose the Variational Causal Autoencoder (VCAUSE), a novel class of variational graph autoencoders for causal inference in the absence of hidden confounders, when only observational data and the causal graph are available.
