6 papers
Neurosymbolic Learning for Inference-Time Argumentation
Gabriel Freedman, Adam Dejl, Adam Gould +4
Claim verification is an important problem in high-stakes settings, including health and finance. When information underpinning claims is incomplete or conflicting, uncertain answe…
Deep Arguing
Adam Gould, Francesca Toni
Deep learning has become the dominant approach for creating high capacity, scalable models across diverse data modalities. However, because these models rely on a large number of l…
Object-Centric Case-Based Reasoning via Argumentation
Gabriel de Olim Gaul, Adam Gould, Avinash Kori +1
We introduce Slot Attention Argumentation for Case-Based Reasoning (SAA-CBR), a novel neuro-symbolic pipeline for image classification that integrates object-centric learning via a…
Supported Abstract Argumentation for Case-Based Reasoning
Adam Gould, Gabriel de Olim Gaul, Francesca Toni
We introduce Supported Abstract Argumentation for Case-Based Reasoning (sAA-CBR), a binary classification model in which past cases engage in debates by arguing in favour of their…
Neuro-Argumentative Learning with Case-Based Reasoning
Adam Gould, Francesca Toni
We introduce Gradual Abstract Argumentation for Case-Based Reasoning (Gradual AA-CBR), a data-driven, neurosymbolic classification model in which the outcome is determined by an ar…
Preference-Based Abstract Argumentation for Case-Based Reasoning (with Appendix)
Adam Gould, Guilherme Paulino-Passos, Seema Dadhania +2
In the pursuit of enhancing the efficacy and flexibility of interpretable, data-driven classification models, this work introduces a novel incorporation of user-defined preferences…