Explainability
Language model activations entangle concepts that mediate their behavior, making it difficult to interpret these factors, which has …
Explainability and transparency of AI systems are undeniably important, leading to several research studies and tools addressing them. …
We propose an interpretable local surrogate (ILS) method for understanding the predictions of black-box graph models. Explainability …
We outline three research directions towards the practical implementation of explainable, sensible and virtuous chatbots for the …
Black-box machine learning (ML) models have become increasingly popular in practice. They can offer great performance, especially in …
Explainability for machine learning models has gained considerable attention within the research community given the importance of …
In this work, we focus on the use of influence functions to identify relevant training examples that one might hope …