24 citations · 95 across the 28 of their papers we have counts for
3 papers · 1 filter
Causal Abstraction with Soft Interventions
Riccardo Massidda, Atticus Geiger, Thomas Icard +1
Causal abstraction provides a theory describing how several causal models can represent the same system at different levels of detail. Existing theoretical proposals limit the anal…
Causal Proxy Models for Concept-Based Model Explanations
Zhengxuan Wu, Karel D'Oosterlinck, Atticus Geiger +2
Explainability methods for NLP systems encounter a version of the fundamental problem of causal inference: for a given ground-truth input text, we never truly observe the counterfa…
CEBaB: Estimating the Causal Effects of Real-World Concepts on NLP Model Behavior
Eldar David Abraham, Karel D'Oosterlinck, Amir Feder +5
The increasing size and complexity of modern ML systems has improved their predictive capabilities but made their behavior harder to explain. Many techniques for model explanation…