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SciTrue: Reliable Scientific Claim Validation with Frontier and Open Language Models at the NTCIR SciClaimEval Task

arXiv · AI, language, vision and robotics · article · Sep 1, 2026 · UTC

We describe the SciTrue team's participation in both subtasks of the NTCIR-19 SciClaimEval task~\cite{sciclaimeval}, which asks systems to verify scientific claims against the tables and figures of a paper. Rather than tuning a single model, we benchmark eleven frontier and open multimodal models under one honest, per-sample protocol and combine them with light, transparent post-processing. On the official, blind test leaderboard (Section~\ref{sec:results}), SciTrue placed first by a clear margin in three of the four evidence-category/subtask combinations, and tied for first on the primary met

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Evidence & attribution

arXiv · AI, language, vision and robotics · 2026-09-01T03:30:45.000Z

First collected: 2026-09-21T06:21:59.299Z. This is not the publication date.