36 citations · 36 across the 1 of their papers we have counts for
3 papers
The Struggles of Feature-Based Explanations: Shapley Values vs. Minimal Sufficient Subsets
Oana-Maria Camburu, Eleonora Giunchiglia, Jakob Foerster +2
For neural models to garner widespread public trust and ensure fairness, we must have human-intelligible explanations for their predictions. Recently, an increasing number of works…
Knowledge Graph Extraction from Videos
Louis Mahon, Eleonora Giunchiglia, Bowen Li +1
Nearly all existing techniques for automated video annotation (or captioning) describe videos using natural language sentences. However, this has several shortcomings: (i) it is ve…
Can I Trust the Explainer? Verifying Post-hoc Explanatory Methods
Oana-Maria Camburu, Eleonora Giunchiglia, Jakob Foerster +2
For AI systems to garner widespread public acceptance, we must develop methods capable of explaining the decisions of black-box models such as neural networks. In this work, we ide…