Large Language Models ↔ neuro-symbolic integration

Relations (1)

related 0.20 — supporting 2 facts

Large Language Models are related to neuro-symbolic integration because they are core components of the MRKL systems architecture, which combines these models with discrete reasoning as described in [1] and [2].

Facts (2)

Sources

The Synergy of Symbolic and Connectionist AI in LLM-Empowered ... arxiv.org arXiv 1 fact

referenceEhud Karpas et al. proposed MRKL systems, a modular, neuro-symbolic architecture that integrates large language models with external knowledge sources and discrete reasoning capabilities.

Neuro-Symbolic AI: Explainability, Challenges, and Future Trends arxiv.org arXiv 1 fact

referenceEhud Karpas, Omri Abend, Yonatan Belinkov, Barak Lenz, Opher Lieber, Nir Ratner, Yoav Shoham, Hofit Bata, Yoav Levine, Kevin Leyton-Brown, et al. authored 'MRKL Systems: A modular, neuro-symbolic architecture that combines large language models, external knowledge sources and discrete reasoning', published as an arXiv preprint (arXiv:2205.00445) in 2022.