Keywords
finance
Abstract
This review examines latent graph reasoning across molecular structure and financial evidence through an evidence-centered design lens. The analysis asks how trajectory diversity should support rather than obscure review. It treats the relevant unit as a complete pathway from data or physical observations to representation, model output, human interpretation, and accountable action. The cited literature is synthesized without inventing experiments or unreported performance values. Particular attention is given to optimization producing diverse but uninformative rationales. The review argues that credible translation requires explicit evidence boundaries, uncertainty-aware evaluation, author-visible traceability, and a documented route for intervention. The resulting framework supports molecular and financial risk analysis while distinguishing component promise from system readiness.
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