5 papers
LTLZinc: a Benchmarking Framework for Continual Learning and Neuro-Symbolic Temporal Reasoning
Luca Salvatore Lorello, Nikolaos Manginas, Marco Lippi +1
Neuro-symbolic artificial intelligence aims to combine neural architectures with symbolic approaches that can represent knowledge in a human-interpretable formalism. Continual lear…
A Scalable Approach to Probabilistic Neuro-Symbolic Robustness Verification
Vasileios Manginas, Nikolaos Manginas, Edward Stevinson +4
Neuro-Symbolic Artificial Intelligence (NeSy AI) has emerged as a promising direction for integrating neural learning with symbolic reasoning. Typically, in the probabilistic varia…
NeSyA: Neurosymbolic Automata
Nikolaos Manginas, George Paliouras, Luc De Raedt
Neurosymbolic (NeSy) AI has emerged as a promising direction to integrate neural and symbolic reasoning. Unfortunately, little effort has been given to developing NeSy systems tail…
Regulatory Compliance through Doc2Doc Information Retrieval: A case study in EU/UK legislation where text similarity has limitations
Ilias Chalkidis, Manos Fergadiotis, Nikolaos Manginas +2
Major scandals in corporate history have urged the need for regulatory compliance, where organizations need to ensure that their controls (processes) comply with relevant laws, reg…
Layer-wise Guided Training for BERT: Learning Incrementally Refined Document Representations
Nikolaos Manginas, Ilias Chalkidis, Prodromos Malakasiotis
Although BERT is widely used by the NLP community, little is known about its inner workings. Several attempts have been made to shed light on certain aspects of BERT, often with co…