When Does a Second Model Help? Cross-Model Review in LLM Verification
Large language models now generate code, documentation, and analyses, and are increasingly used to review such output. We ask when a second review by a different model helps. Building on the author's earlier preprints, which varied context, repetition, and role structure within one model, we test model independence in a controlled experiment: 30 artifacts with 150 planted errors, 10 review conditions, and 900 review sessions with three reviewer models from two developers. In this experiment, (1) a top-tier cross-model reviewer is not significantly different in F1 from same-model review in a fresh session (CCR), which does not establish equivalence; (2) the two find partly different errors...
| Authors | Tae-Eun Song |
|---|---|
| Primary category | cs.CL |
| Published | 1 October 2026 |
| Last updated at source | 6 October 2026 |
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