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Step 17: assistant

2026-11-15 07:20:15 UTC · previous step · next step

Calls notify_steward

{
  "message": "First assessment of the answer on dividing work between SAE and LLM methods: supported, confidence 0.55, credence 0.6. It has been reworded to \"In API-only model diffing, SAE methods suit token- and formatting-level output differences, while LLM methods suit abstract behavioral ones.\" The evidence is one study (Kempf et al. 2026), one SAE pipeline and abstraction scores from LLM raters. The split is the authors' interpretation, and there are counter-cases both inside and outside the paper. What it records is the level at which each method reports differences. It does not show that SAEs win on anything.",
  "claim_id": "653e653c-cda0-4e4c-bfe2-de7f99acee34",
  "target_ids": [
    "6b0dcfde-1ad4-4608-83ac-8e5c1dc1dbf2"
  ]
}