Author

Koji Tsuda

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Review Aug 2026

AutoSchema: Live Schema Grounding for Agentic Text-to-Sparql over Heterogeneous Knowledge Graphs

autoschema improves mean factoid accuracy over TogoMCP in the biomedical KGQA tasks and gives consistent gains in the longitudinal BioASQ evaluation, and reduces iteration budget exhaustion and uses fewer tool calls on average in the core evaluation.

Yi-Ming Zhang, Koji Tsuda · 0 citations

Jul 2026

SAGA: Schema-Aware Grounding for Agentic Text-to-SPARQL Generation

AGA is proposed, a training-free framework that turns property exploration into a schema-constrained grounding operation, and achieves the highest F1 on all nine settings and the highest exact-match accuracy on eight, while reducing empty-result queries across all reported Wikidata settings.

Yi-Ming Zhang, Koji Tsuda · arXiv.org · 0 citations