The Role of Foundation Models in Neuro-Symbolic Learning and Reasoning

Neuro-Symbolic AI (NeSy) holds promise to ensure the safe deployment of AI systems, as interpretable symbolic techniques provide formal behaviour guarantees. The challenge is how to effectively integrate neural and symbolic computation, to enable learning and reasoning from raw data. Existing pipelines that train the neural and symbolic components sequentially require extensive labelling, whereas end-to-end approaches are limited in terms of scalability, due to the combinatorial explosion in the symbol grounding problem. In this paper, we leverage the implicit knowledge …

ai systems challenge components computation cs.ai cs.lg data deployment foundation neuro neuro-symbolic ai pipelines raw reasoning role symbolic ai systems train