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AI is dramatically lowering the cost of reading papers, writing code, and running experiments. But as research output explodes, telling which results can be trusted keeps getting harder. CiteArk connects the claims in scientific papers with their experimental conditions, execution process, result evidence, and verification records, so researchers and agents can verify claims, reuse experimental results, and build follow-up research on them instead of repeating work. We hope these trustworthy research records will grow into a scientific foundation that researchers, labs, and agents can all build on together.

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When Tool Calls Succeed but Workflows Fail: Anomalies at the Agent–Tool Boundary · CiteArk

When Tool Calls Succeed but Workflows Fail: Anomalies at the Agent–Tool Boundary

PublicScope: Light

Authors:Artem Trofimov, Boris Novikov

arXiv 2026 Artificial Intelligence Databases Distributed, Parallel, and Cluster Computing Software Engineering

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150 files · 1.3 MB

CCiteArk CAP 1.0 Verified RunnerVerification runnerImport verified CAP 1.0 research Artifact—Current version

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README.md16 KB

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