3 citations · 10 across the 9 of their papers we have counts for
Showing 2024Show all
2 papers · 1 filter
cs.AI2024★ 1 cited
The Role of Foundation Models in Neuro-Symbolic Learning and Reasoning
Daniel Cunnington, Mark Law, Jorge Lobo +1
Neuro-Symbolic AI (NeSy) holds promise to ensure the safe deployment of AI systems, as interpretable symbolic techniques provide formal behaviour guarantees. The challenge is how t…
cs.LG2024
Can we Constrain Concept Bottleneck Models to Learn Semantically Meaningful Input Features?
Jack Furby, Daniel Cunnington, Dave Braines +1
Concept Bottleneck Models (CBMs) are regarded as inherently interpretable because they first predict a set of human-defined concepts which are used to predict a task label. For inh…