6 papers
Selective Fine-Tuning for Targeted and Robust Concept Unlearning
Mansi, Avinash Kori, Francesca Toni +1
Text guided diffusion models are used by millions of users, but can be easily exploited to produce harmful content. Concept unlearning methods aim at reducing the models' likelihoo…
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…
Transparent Visual Reasoning via Object-Centric Agent Collaboration
Benjamin Teoh, Ben Glocker, Francesca Toni +1
A central challenge in explainable AI, particularly in the visual domain, is producing explanations grounded in human-understandable concepts. To tackle this, we introduce OCEAN (O…
Object-Centric Neuro-Argumentative Learning
Abdul Rahman Jacob, Avinash Kori, Emanuele De Angelis +3
Over the last decade, as we rely more on deep learning technologies to make critical decisions, concerns regarding their safety, reliability and interpretability have emerged. We i…
Identifiable Object Representations under Spatial Ambiguities
Avinash Kori, Francesca Toni, Ben Glocker
Modular object-centric representations are essential for *human-like reasoning* but are challenging to obtain under spatial ambiguities, *e.g. due to occlusions and view ambiguitie…
Identifiable Object-Centric Representation Learning via Probabilistic Slot Attention
Avinash Kori, Francesco Locatello, Ainkaran Santhirasekaram +3
Learning modular object-centric representations is crucial for systematic generalization. Existing methods show promising object-binding capabilities empirically, but theoretical i…