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 (VEs) for large-scale RDF Knowledge Graphs, focusing on the widely used DrugBank dataset. The study aims to reduce the computational burden and environmental impact associated with repeatedly generating embeddings for downstream tasks such as lin...
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...
We present EXYGEN (EXplore Your Graphs ENgine), a framework for knowledge graph (KG) understanding that enables conversational access to KGs at scale. We address two questions in sequence. First, how effectively can LLMs perform text-to-SPARQL generation given only automatically derived structured metadata and small gr...
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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