English

Stage-Audit: Auditable Source-Frontier Discovery for Cross-Wiki Tables

Computation and Language 2026-05-21 v1

Abstract

LLM-curated tables can appear source-grounded while containing unsupported rows: the curator may recall entries from parametric memory and retroactively attach page-level citations that are not the actual source. We study this hazard in Seed2Frontier discovery: the task of finding complement Wikipedia pages from a seed page to assemble a structured table. Stage-Audit addresses it with disjoint curator-auditor write rights, a row-level source-citation gate, and a 12-check audit taxonomy over keys, schema, source roles, cardinality, and scope. On a curated 51-instance Seed2Frontier evaluation set spanning 15 top-level domains, Stage-Audit improves source-frontier precision over a vanilla LLM curator from 0.356 to 0.505 (+42% relative) and F1 from 0.334 to 0.451 (+35%), while maintaining explicit per-row source traceability. The vanilla-LLM-vs-Stage-Audit comparison isolates the policy contribution rather than LLM-based discovery in general.

Keywords

Cite

@article{arxiv.2605.20478,
  title  = {Stage-Audit: Auditable Source-Frontier Discovery for Cross-Wiki Tables},
  author = {Chen Shen},
  journal= {arXiv preprint arXiv:2605.20478},
  year   = {2026}
}

Comments

9 pages, 2 figures, 3 tables. Accepted at the ACM CAIS 2026 Workshop on AI Agents for Discovery in the Wild