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cs.AI2025
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…
cs.AI2025
A Neuro-Symbolic Framework for Sequence Classification with Relational and Temporal Knowledge
Luca Salvatore Lorello, Marco Lippi, Stefano Melacci
One of the goals of neuro-symbolic artificial intelligence is to exploit background knowledge to improve the performance of learning tasks. However, most of the existing frameworks…
cs.AI2024
The KANDY Benchmark: Incremental Neuro-Symbolic Learning and Reasoning with Kandinsky Patterns
Luca Salvatore Lorello, Marco Lippi, Stefano Melacci
Artificial intelligence is continuously seeking novel challenges and benchmarks to effectively measure performance and to advance the state-of-the-art. In this paper we introduce K…