13 citations · 20 across the 4 of their papers we have counts for
4 papers
What Do Large Language Models Know? Tacit Knowledge as a Potential Causal-Explanatory Structure
Céline Budding
It is sometimes assumed that Large Language Models (LLMs) know language, or for example that they know that Paris is the capital of France. But what -- if anything -- do LLMs actua…
Benchmarking the Influence of Pre-training on Explanation Performance in MR Image Classification
Marta Oliveira, Rick Wilming, Benedict Clark +4
Convolutional Neural Networks (CNNs) are frequently and successfully used in medical prediction tasks. They are often used in combination with transfer learning, leading to improve…
Evaluating saliency methods on artificial data with different background types
Céline Budding, Fabian Eitel, Kerstin Ritter +1
Over the last years, many 'explainable artificial intelligence' (xAI) approaches have been developed, but these have not always been objectively evaluated. To evaluate the quality…
Scrutinizing XAI using linear ground-truth data with suppressor variables
Rick Wilming, Céline Budding, Klaus-Robert Müller +1
Machine learning (ML) is increasingly often used to inform high-stakes decisions. As complex ML models (e.g., deep neural networks) are often considered black boxes, a wealth of pr…