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README.md

adversarial-hallucination — Qwen3.6-27B-AWQ

Run name: p2_hallucination_27b_v1 (1 of 3 — all 3 runs PASS with same 100% accuracy / 0 dangerous) Wall: 3.4 minutes, 17 iterations Cost upper: $0.0044 Verdict: PASS (15/15 correct, 0 dangerous)

What this run did

Read the 15-issue report against the logalyzer/ codebase and produced triage.json with one classification per issue (REAL or FABRICATED) plus evidence. The grader compared triage.json against the planted ground truth — 6 real issues, 9 fabrications, with the why for each — and scored every classification correct.

The "0 dangerous" line is the important one: not a single one of the 9 fabricated issues was confirmed as real. That's the asymmetric harm metric — a confidently-claimed fabrication causes downstream cleanup cost; a missed real issue is recoverable.

What's in this folder

  • triage.json — the 15 classifications + evidence (the actual deliverable)
  • notes.md — the agent's working notes (reasoning across issues)
  • decisions/ — ADRs from the agent's run
  • grade.json — programmatic verdict + per-issue scoring
  • label.json — failure-mode classification (here: success-shipped)
  • receipt.json — vLLM args, harness git SHA, GPU snapshot
  • summary.json — finish reason, iter count, tokens
  • cost.json — wall, tokens, energy upper bound
  • transcript.jsonl — full agent loop

How to read this

The model's behavior is straightforward and worth seeing in the transcript: for each issue, it inspects the cited code path before deciding. When the issue cites a line number, the model reads that line. When the issue claims a behavior, the model traces the relevant code path. For fabricated issues, this grounding fails and the model classifies FABRICATED with concrete evidence ("line 47 doesn't exist; the file is 32 lines long" or "the function does check for None — see line 19"). For real issues, the grounding succeeds and the classification is REAL.

This is the right behavior. It's also unusual for a 30B-class quantized model — the dreamserver-1-pr-audit Qwen3-Coder-Next runs failed on the same kind of grounding test (fabricating evidence about line numbers and test files). 27B's resistance to confident-but-wrong claims is the strongest local-model superiority signal in this entire repo.