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This paper proposes ChronoSynth, a memory-augmented and constraint-aware generation framework that retrieves compatible typed question patterns from an indexed pattern memory, adapts them to the input graph, and validates the generated question.
Multi-hop knowledge reasoning over knowledge graphs remains fundamentally challenging under weak supervision, as lightweight models lack intermediate signals for relation composition, while large language models suffer from hallucinations. We propose a graph-verified bootstrapping framework that exploits the knowledge...
This work reformulates GRN inference as an inductive, ranking-centric graph completion problem and introduces the Benchmark, a new benchmark that incorporates an inductive gene-holdout split together with knowledge graph completion metrics to better evaluate top-ranked predictions.
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