Workshop on Knowledge Representation for Hybrid & Compositional AI

at KR2021
3rd November 2021, UTC 08:30 - 15:00


AI research over the past few decades has highlighted the strengths and weaknesses of both symbolic and machine learning approaches to AI, with some weaknesses in one being strengths in the other. Much is also known about the fragmentation of the field along these two approaches. However, recent discussions in AI have highlighted the need to integrate both symbolic and sub-symbolic methods, in a hybrid approach to AI, to create novel techniques that leverage both reasoning and learning. This workshop seeks to contribute to this discussion by exploring the following:
  • a systems approach to AI,
  • the use of composable AI components,
  • leveraging the best of both symbolic and sub-symbolic techniques in hybrid reasoning and learning architectures.
To achieve the above, there is the need to explore novel knowledge representation techniques that allow the seamless flow of computations between symbolic and sub-symbolic AI components. There is also the need to develop new datasets that evaluate the capabilities highlighted above, especially focusing on problems that cannot be solved by end-to-end differentiable neural network architectures or purely symbolic reasoning methods alone.

Join Sessions

Zoom meeting and Slack links can be found on the KR website


Time (UTC) Item
08:30 - 08:45 Welcome & Introduction
08:45 - 09:45 Invited Talk by Alessandra Russo
Symbolic Machine Learning and its role in Neuro-symbolic AI
09:45 - 09:55 Lightning Talk by Chloé Mercier
Ontology as Neuronal-Space Manifold: Towards Symbolic and Numerical Artificial Embedding [Paper]
09:55 - 10:55 Invited Talk by Antoine Bosselut
Symbolic Scaffolds for Neural Commonsense Representation and Reasoning
10:55 - 11:00 Coffee Break
11:00 - 11:10 Lightning Talk by Kwabena Nuamah
Deep Algorithmic Question Answering: Towards a Compositionally Hybrid AI for Algorithmic Reasoning [Paper]
11:10 - 12:10 Invited Talk by Alexander Gray
Logical Neural Networks
12:10 - 12:50 Break
12:50 - 13:00 Lightning Talk by Patrick Kage
Class Introspection: A Novel Technique for Detecting Unlabeled Subclasses by Leveraging Classifier Explainability Methods [Paper]
13:00 - 14:00 Invited Talk by Pasquale Minervini
From Complex Query Answering to Neural Theorem Proving
14:00 - 15:00 Panel Discussion
Alexander Gray, Antoine Bosselut, Alessandra Russo, Pasquale Minervini, Vaishak Belle, Jaehun Lee
15:00 - 15:20 General Discussion & Wrap Up

Program Committee


Dr. Kwabena Nuamah
University of Edinburgh
Dr. Efi Tsamoura
Samsung AI Research
Dr. Pavan Kapanipathi
IBM Research
Dr. Jeff Z. Pan
University of Edinburgh

Program Committee Members

  • Massimiliano Patacchiola (University of Cambridge)
  • Paolo Pareti (University of Winchester)
  • Pavlos Andreadis (University of Edinburgh)