Step 25: assistant

thinking

Calls read_page

{
  "url": "https://github.com/marijanikolicds/spar-fa26-blackbox-sandbagging-cedar",
  "offset": 3000,
  "max_chars": 12000
}

Calls add_argument

{
  "name": "The argument from the imitation-trained sandbagger",
  "stance": "for",
  "claim_id": "022b9cef-1397-4f4c-af7e-917df64bab6b",
  "description": "A sandbagger trained to reproduce a weaker model's outputs leaves nothing in its outputs to find, so output-only detection depends on the sandbagger leaking its intent or behaving inconsistently."
}

Calls add_argument

{
  "name": "The argument from other output artifacts",
  "stance": "against",
  "claim_id": "022b9cef-1397-4f4c-af7e-917df64bab6b",
  "description": "Output-only detectors have separated sandbaggers from weaker models using signals that are neither stated intent nor paraphrase inconsistency, so the two named conditions are not the only ones."
}

Calls add_argument

{
  "name": "The argument that the two named signals are not themselves reliable",
  "stance": "against",
  "claim_id": "022b9cef-1397-4f4c-af7e-917df64bab6b",
  "description": "Reasoning monitors and paraphrase-consistency checks miss a large share of sandbagging even where their signal is present, so the claim's two conditions do not mark out a region of reliable detection."
}