14 citations · 14 across the 2 of their papers we have counts for
2 papers
cs.LG2026
Concept Flow Models: Anchoring Concept-Based Reasoning with Hierarchical Bottlenecks
Ya Wang, Adrian Paschke
Concept Bottleneck Models (CBMs) enhance interpretability by projecting learned features into a human-understandable concept space. Recent approaches leverage vision-language model…
cs.LG2022★ 14 cited
Knowledge Augmented Machine Learning with Applications in Autonomous Driving: A Survey
Julian Wörmann, Daniel Bogdoll, Christian Brunner +49
The availability of representative datasets is an essential prerequisite for many successful artificial intelligence and machine learning models. However, in real life applications…