Scientists aim to discover meaningful formulae that accurately describe experimental data.
Mathematical models of natural phenomena can be manually created from domain …

The interaction decoder utilized in prevalent Transformer-based HOI detectors typically
accepts pre-composed human-object pairs as inputs. Though achieving remarkable …

We introduce the novel Diffusion Visual Programmer (DVP), a neuro-symbolic image
translation framework. Our proposed DVP seamlessly embeds a condition-flexible diffusion …

Knowledge graphs, as understood within the Semantic Web and Knowledge Representation
communities, are more than just graph data. OWL-based knowledge graphs offer the …

We address a key challenge for neuro-symbolic (NeSy) systems by leveraging convex and
bilevel optimization techniques to develop a general gradient-based framework for end-to …

Neuro-symbolic systems combine the abilities of neural perception and logical reasoning.
However, end-to-end learning of neuro-symbolic systems is still an unsolved challenge. This …

Recent advances in Hierarchical Multi-label Classification (HMC), particularly
neurosymbolic-based approaches, have demonstrated improved consistency and accuracy …

Metacognition is the concept of reasoning about an agent's own internal processes and was
originally introduced in the field of developmental psychology. In this position paper, we …

The field of Neural-Symbolic (NeSy) systems is growing rapidly. Proposed approaches show
great promise in achieving symbiotic unions of neural and symbolic methods. However …

Neural networks find applications in many safety-critical systems that raise concerns about
their deployment: Are we sure the network will never advise doing anything violating a set of …