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arxiv: 2605.20478 · v1 · pith:26LLNQ3Enew · submitted 2026-05-19 · 💻 cs.CL

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

Chen Shen This is my paper

Pith reviewed 2026-05-21 07:10 UTC · model grok-4.3

classification 💻 cs.CL
keywords LLM table curationsource verificationSeed2Frontier discoveryaudit taxonomycross-wiki tablesrow-level citationunsupported rowsWikipedia data extraction
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The pith

Stage-Audit separates curator and auditor roles with a row-level source gate and 12-check taxonomy to reduce unsupported rows in LLM-built cross-wiki tables.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper examines how LLM curators can assemble tables that look source-grounded yet include rows drawn from parametric memory rather than the cited pages. It introduces Stage-Audit to counter this by assigning disjoint write rights to the curator and auditor, enforcing a row-level source-citation gate, and applying a fixed 12-check audit taxonomy that examines keys, schema, source roles, cardinality, and scope. On a 51-instance Seed2Frontier test set drawn from 15 top-level domains, the approach raises source-frontier precision from 0.356 to 0.505 and F1 from 0.334 to 0.451 while preserving explicit per-row traceability. A sympathetic reader would care because many downstream applications treat LLM-generated tables as reliable inputs for further reasoning or data integration. The comparison isolates the contribution of the audit policy itself rather than the underlying discovery model.

Core claim

Stage-Audit addresses the hazard in Seed2Frontier discovery where an LLM curator may recall entries from parametric memory and retroactively attach page-level citations that are not the actual source, by introducing 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, which on a curated 51-instance evaluation set improves source-frontier precision over a vanilla LLM curator from 0.356 to 0.505 and F1 from 0.334 to 0.451 while maintaining explicit per-row source traceability.

What carries the argument

Disjoint curator-auditor write rights together with a row-level source-citation gate and the 12-check audit taxonomy that inspects keys, schema, source roles, cardinality, and scope.

If this is right

  • Tables produced under Stage-Audit carry explicit per-row source traceability that survives downstream reuse.
  • The same curator-auditor split and taxonomy can be applied to other table-assembly tasks that start from seed pages.
  • Precision gains are attributable to the audit policy rather than to any particular LLM-based discovery method.
  • The 12-check taxonomy provides a reusable checklist for human or automated verification of source roles and cardinality.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • The audit layer could be inserted into existing LLM table pipelines without retraining the underlying model.
  • If the taxonomy proves stable across languages, the method might extend to cross-lingual table construction from Wikipedia.
  • The separation of roles suggests a general pattern for making other LLM output streams auditable at the level of individual facts.
  • Future work could test whether relaxing any of the 12 checks trades measurable precision for lower audit cost.

Load-bearing premise

The 51-instance evaluation set and the 12-check audit taxonomy are representative enough that the measured precision gain reflects a general reduction in unsupported rows rather than an artifact of the chosen domains or the specific way auditors apply the checks.

What would settle it

A replication on a fresh collection of at least 100 Seed2Frontier instances drawn from domains outside the original 15 top-level domains that shows no improvement in source-frontier precision under the same audit policy would falsify the central claim.

Figures

Figures reproduced from arXiv: 2605.20478 by Chen Shen.

Figure 1
Figure 1. Figure 1: Stage–Audit walkthrough on a curated Seed2Frontier instance. The curator proposes [PITH_FULL_IMAGE:figures/full_fig_p003_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: Severity taxonomy applied to the 182 Stage–Audit auditor findings on the 51-instance set [PITH_FULL_IMAGE:figures/full_fig_p008_2.png] view at source ↗
read the original 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.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The manuscript introduces Stage-Audit, a framework for auditable source-frontier discovery when constructing cross-Wiki tables from seed pages. It employs disjoint curator-auditor write rights, a row-level source-citation gate, and a 12-check audit taxonomy covering keys, schema, source roles, cardinality, and scope. On a curated 51-instance Seed2Frontier evaluation set spanning 15 top-level domains, Stage-Audit is reported to raise source-frontier precision from 0.356 to 0.505 (+42% relative) and F1 from 0.334 to 0.451 (+35%) relative to a vanilla LLM curator while preserving explicit per-row traceability. The comparison is presented as isolating the contribution of the audit policy.

Significance. If the measured gains prove robust to evaluation construction and auditor variability, the work would offer a concrete mechanism for reducing unsupported rows in LLM-generated structured outputs. The emphasis on disjoint rights and row-level citation traceability is a constructive contribution to reliable knowledge discovery pipelines.

major comments (2)
  1. [Evaluation] Evaluation section: the central precision and F1 lifts are measured on a 51-instance curated set without reported inter-annotator agreement for the 12-check taxonomy or statistical significance tests; this leaves open whether the observed deltas (0.356→0.505, 0.334→0.451) reflect the Stage-Audit policy or properties of the chosen seeds, domains, and auditor application.
  2. [§5] §5 (or equivalent baseline description): the vanilla-LLM curator prompting strategy is not detailed, so it is unclear whether the reported improvement isolates the disjoint-rights and citation-gate policy or simply differences in prompt engineering.
minor comments (2)
  1. [Abstract] The abstract and evaluation description should explicitly state the curation criteria and domain-stratified breakdown to allow readers to assess selection bias.
  2. [Results] Table or figure reporting the per-check audit outcomes would help readers see which of the 12 checks drive the measured improvement.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the constructive feedback. We address each major comment below and will revise the manuscript accordingly to improve clarity and robustness.

read point-by-point responses

  1. Referee: [Evaluation] Evaluation section: the central precision and F1 lifts are measured on a 51-instance curated set without reported inter-annotator agreement for the 12-check taxonomy or statistical significance tests; this leaves open whether the observed deltas (0.356→0.505, 0.334→0.451) reflect the Stage-Audit policy or properties of the chosen seeds, domains, and auditor application.

    Authors: We agree that the absence of inter-annotator agreement (IAA) metrics and statistical significance tests is a limitation that should be addressed. In the revised version, we will report IAA (e.g., Cohen's kappa) for the 12-check taxonomy by having a second annotator independently audit a random subset of the 51 instances. We will also add statistical significance testing, such as McNemar's test for paired proportions or bootstrap confidence intervals, to evaluate whether the precision and F1 improvements are significant. These additions will help confirm that the deltas are attributable to the Stage-Audit policy rather than seed selection or auditor-specific factors. revision: yes

  2. Referee: [§5] §5 (or equivalent baseline description): the vanilla-LLM curator prompting strategy is not detailed, so it is unclear whether the reported improvement isolates the disjoint-rights and citation-gate policy or simply differences in prompt engineering.

    Authors: We concur that the vanilla-LLM curator baseline prompting must be specified in detail to isolate the contribution of the disjoint-rights and row-level source-citation gate. In the revision, we will expand the baseline description in §5 (or the equivalent section) to include the complete prompt templates for the vanilla curator. We will explicitly contrast these with the Stage-Audit prompts, emphasizing the absence of disjoint write rights and the row-level gate in the baseline. This will clarify that the reported gains derive from the audit policy rather than prompt variations. revision: yes

Circularity Check

0 steps flagged

No significant circularity; empirical comparison is self-contained

full rationale

The paper reports measured precision and F1 gains on a held-out 51-instance Seed2Frontier evaluation set against an external vanilla-LLM baseline. No equations, fitted parameters, or derivations are present that reduce the reported deltas to inputs by construction. The central claim rests on the disjoint curator-auditor policy and 12-check taxonomy applied to an explicitly curated test collection; this is an empirical result rather than a self-referential definition or self-citation load-bearing step. No self-citations, ansatzes, or uniqueness theorems appear in the provided text that would trigger any of the enumerated circularity patterns.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 0 invented entities

The approach rests on the domain assumption that Wikipedia pages constitute reliable, checkable sources and that a fixed 12-check taxonomy can catch the main failure modes of LLM curation without missing systematic gaps.

axioms (2)
  • domain assumption Wikipedia pages provide ground-truth sources that can be audited for row-level support
    Invoked when the paper defines source-frontier discovery and row-level citation gates
  • ad hoc to paper The 12-check audit taxonomy is comprehensive for keys, schema, source roles, cardinality, and scope
    The taxonomy is introduced as the core auditing instrument without external validation cited

pith-pipeline@v0.9.0 · 5697 in / 1361 out tokens · 33600 ms · 2026-05-21T07:10:13.913193+00:00 · methodology

discussion (0)

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