EchoAudit Assessing reports from incomplete evidence
Nathan Samson · Team EchoAudit
Submitted to AI Collusion Research Sprint. Sprint projects are early-stage work by participants, not Apart Research publications.
An evidence auditor may receive an invoice report and only part of its supporting ledger. Missing records sometimes prevent a justified verdict, yet the visible subtotal can already disprove a claimed total. We constructed twelve ledger families that separate these situations while holding partial source evidence fixed. Each family supplies an unresolved report, two complete source versions with opposite correctness, and a partial report below the visible subtotal. Three scripted message contexts accompany each view, producing 144 assessments per configuration. Qwen3-8B in nonthinking mode returned valid structured outputs on all 144 calls and accurately assessed 71/72 complete source cases. It gave no warranted abstentions on 36 unresolved cases. None of 36 context pairs combined warranted abstention with rejection of the partial but refutable claim. A subsequently selected Claude Sonnet 5.5 configuration with adaptive thinking received the same instruction and evidence strings on the same families. It accurately assessed 65/72 complete source cases, but only 81/144 responses passed the unchanged output contract. Its joint partial score was 1/36, with 35/36 unresolved responses invalid. These output failures limit a semantic comparison between configurations. The diagnostic separates complete source reconciliation, evidence sufficiency and valid answer production within a small synthetic domain.
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@misc{samson2026echoaudit,
title = {{EchoAudit Assessing reports from incomplete evidence}},
author = {Nathan Samson},
year = {2026},
month = oct,
note = {Submitted to AI Collusion Research Sprint, an Apart Research Sprint},
howpublished = {\url{https://apartresearch.com/sprints/projects/echoaudit-assessing-reports-from-incomplete-evidence-jj4l}},
url = {https://apartresearch.com/sprints/projects/echoaudit-assessing-reports-from-incomplete-evidence-jj4l}
}More from AI Collusion Research Sprint
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