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Yair Ori Gat

2 accepted papers

2024

Faithful Explanations of Black-box NLP Models Using LLM-generated Counterfactuals

ICLR 2024poster

Causal explanations of the predictions of NLP systems are essential to ensure safety and establish trust. Yet, existing methods often fall short of explaining model predictions effectively or efficiently and are often model-specific. In this paper, we address model-agnostic explanations, proposing t…

Cited by 41SourcePDFScholar
2022

CEBaB: Estimating the Causal Effects of Real-World Concepts on NLP Model Behavior

NeurIPS 2022accept

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 have been developed in response, but we lack clear criteria for assessing these techniques. In this paper, we cast model…

Cited by 54SourcePDFScholar