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Commonsense knowledge and language understanding for multi-hop reasoning

Incorporate commonsense knowledge and advanced language understanding into Neuro-Symbolic systems to enhance multi-hop reasoning capabilities across documents and contexts.

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Background

The paper discusses approaches that generate commonsense inferences and use document links to improve multi-hop language understanding. The authors explicitly list enhancing multi-hop reasoning via commonsense and advanced language understanding as an open question.

References

Open research questions remain around how Neuro-Symbolic AI can develop scalable frameworks that integrate traditional logic programming with neural networks for complex reasoning tasks, incorporate commonsense knowledge and advanced language understanding to enhance multi-hop reasoning capabilities, combine symbolic logic with neural networks to ensure reliable and trustworthy decision-making and integrate meta-cognitive abilities to enable self-monitoring and adjustment of reasoning strategies for clearer, more understandable explanations.

— Neuro-Symbolic AI in 2024: A Systematic Review (2501.05435 - Colelough et al., 9 Jan 2025) in Section 4.4 Logic and Reasoning