Human uncertainty in concept-based ai systems
Placing a human in the loop may help abate the risks of deploying AI systems in safety-
critical settings (eg, a clinician working with a medical AI system). However, mitigating risks …
critical settings (eg, a clinician working with a medical AI system). However, mitigating risks …
Faithful vision-language interpretation via concept bottleneck models
The demand for transparency in healthcare and finance has led to interpretable machine
learning (IML) models, notably the concept bottleneck models (CBMs), valued for their …
learning (IML) models, notably the concept bottleneck models (CBMs), valued for their …
Robust and interpretable medical image classifiers via concept bottleneck models
Medical image classification is a critical problem for healthcare, with the potential to alleviate
the workload of doctors and facilitate diagnoses of patients. However, two challenges arise …
the workload of doctors and facilitate diagnoses of patients. However, two challenges arise …
Learning to receive help: Intervention-aware concept embedding models
Abstract Concept Bottleneck Models (CBMs) tackle the opacity of neural architectures by
constructing and explaining their predictions using a set of high-level concepts. A special …
constructing and explaining their predictions using a set of high-level concepts. A special …
A closer look at the intervention procedure of concept bottleneck models
Abstract Concept bottleneck models (CBMs) are a class of interpretable neural network
models that predict the target response of a given input based on its high-level concepts …
models that predict the target response of a given input based on its high-level concepts …
Improving deep learning with prior knowledge and cognitive models: A survey on enhancing explainability, adversarial robustness and zero-shot learning
F Mumuni, A Mumuni - Cognitive Systems Research, 2024 - Elsevier
We review current and emerging knowledge-informed and brain-inspired cognitive systems
for realizing adversarial defenses, eXplainable Artificial Intelligence (XAI), and zero-shot or …
for realizing adversarial defenses, eXplainable Artificial Intelligence (XAI), and zero-shot or …
Editable concept bottleneck models
Concept Bottleneck Models (CBMs) have garnered much attention for their ability to
elucidate the prediction process through a human-understandable concept layer. However …
elucidate the prediction process through a human-understandable concept layer. However …