Artificial Intelligence(AI): A Cross-Domain Reasoning Framework for Knowledge Innovation: Enhanced Model Composition and Semantic Alignment
Year: 2025
Type: article
Abstract: Discover a new way of scientific exploration! This AI-assisted framework moves beyond conventional language models by generating cross-domain hypotheses and validating them through interpretable reasoning chains. Key features: Structured Knowledge Units: Concepts from Physics, AI, Neuroscience, and more are formalized with inputs, outputs, and formulas. Cross-Domain Innovation: AI maps analogies across fields to propose novel hypotheses. Formula-Driven Reasoning: Hypotheses are validated by deriving testable mathematical relationships. Transparent and Reproducible: Each step is traceable, providing confidence in results. This framework enables researchers to explore new connections, generate scientifically meaningful ideas, and derive formulas automatically, bridging human intuition with AI-powered reasoning. Keywords: Scientific Innovation, Cross-Domain Reasoning, Knowledge Units, Hypothesis Generation, AI Discovery, Interpretable Formulas
Author: Xu, Jingyao
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7085078671
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