5 papers
Reasoning as Data: Representation-Computation Unity and Its Implementation in a Domain-Algebraic Inference Engine
Chao Li, Yuru Wang
Every existing knowledge system separates storage from computation. We show this separation is unnecessary and eliminate it. In a standard triple is_a(Apple, Company), domain conte…
Domain-Contextualized Inference: A Computable Graph Architecture for Explicit-Domain Reasoning
Chao Li, Yuru Wang, Chunyi Zhao
We establish a computation-substrate-agnostic inference architecture in which domain is an explicit first-class computational parameter. This produces domain-scoped pruning that re…
Domain-constrained knowledge representation: A modal framework
Chao Li, Yuru Wang, Chunyi Zhao
Knowledge graphs store large numbers of relations efficiently, but they remain weak at representing a quieter difficulty: the meaning of a concept often shifts with the domain in w…
How should AI knowledge be governed? Epistemic authority, structural transparency, and the case for open cognitive graphs
Chao Li, Chunyi Zhao, Yuru Wang +1
Through widespread use in formative assessment and self-directed learning, educational AI systems exercise de facto epistemic authority. Unlike human educators, however, these syst…
Domain-Contextualized Concept Graphs: A Computable Framework for Knowledge Representation
Chao Li, Yuru Wang
Traditional knowledge graphs are constrained by fixed ontologies that organize concepts within rigid hierarchical structures. The root cause lies in treating domains as implicit co…