Book contents
- Frontmatter
- Contents
- Preface
- 1 Introduction
- 2 Knowledge Graphs for Explainability and Interpretability
- 3 Knowledge-Infused Learning: The Subsumer to NeuroSymbolic AI
- 4 Shallow Infusion of Knowledge
- 5 Semi-deep Infusion Learning
- 6 Deep Knowledge-Infused Learning
- 7 Process Knowledge-Infused Learning
- 8 Knowledge-Infused Conversational NLP
- 9 Neurosymbolic Large Language Models
- References
- Index
5 - Semi-deep Infusion Learning
Published online by Cambridge University Press: 22 April 2026
Book contents
- Frontmatter
- Contents
- Preface
- 1 Introduction
- 2 Knowledge Graphs for Explainability and Interpretability
- 3 Knowledge-Infused Learning: The Subsumer to NeuroSymbolic AI
- 4 Shallow Infusion of Knowledge
- 5 Semi-deep Infusion Learning
- 6 Deep Knowledge-Infused Learning
- 7 Process Knowledge-Infused Learning
- 8 Knowledge-Infused Conversational NLP
- 9 Neurosymbolic Large Language Models
- References
- Index
Summary
Compared to shallow infusion, semi-deep infusion concerns opening the blackbox of AI systems using knowledge sources. This chapter will provide a detailed grounding of model interpretability, highlighting the state-of-theart methods that promise interpretable AI, the limitations of these methods, and how knowledge infusion in AI can help make models interpretable without sacrificing uncertainty while handling context sensitivity, and userlevel explainability.
Information
- Type
- Chapter
- Information
- Knowledge-Infused LearningNeurosymbolic AI for Explainability, Interpretability, and Safety, pp. 94 - 120Publisher: Cambridge University PressPrint publication year: 2026
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