TL;DR
Under the official 3rd-stage 60%/40% NatUKE split, the best CareWeavers configuration per task exceeds the published NatUKE reference baseline on 4 of 5 property types.
This work addresses the need for efficient and reusable vector embeddings for large-scale RDF Knowledge Graphs, focusing on the widely used DrugBank dataset, and provides a comprehensive, reusable resource that facilitates research while promoting computational efficiency and environmental sustainability.
Cross-domain transfer analysis on WebNLG further shows that example-specific pattern overlap and register similarity are stronger predictors of transferability than property-set overlap alone, and long-tail property distributions are identified as the primary performance bottleneck.
Motivation Machine learning has emerged as a powerful accelerator for identifying PET-hydrolyzing enzymes (PETases). Yet, published models are often evaluated on benchmark performance alone, leaving their biological validity unexamined. Here we present InterPET, a curated benchmark and ablation study addressing both is...
Results show that structured schema context and lightweight prompting can substantially reduce reliance on fine-tuning for scalable conversational access to KGs, though closing the remaining gap to fully fine-tuned approaches will likely require reducing dependence on curated question-query exemplars.
This work introduces MolBioKG, a two-layer system that grounds unseen molecules in biomedical evidence via multi-resolution structural anchoring and outperforms strong baselines across in-graph link recovery, complex multi-hop reasoning, and out-of-graph generalization.
This method induces Horn rules from target-relation-guided random walks and assigns each candidate a reliability score that combines smoothed rule confidence, normalized support, path consistency, type validity, and redundancy.
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