Step 13: assistant

Calls write_argument

{
  "content": "Li et al. (August 2026) ran seven frontier models (including GPT-5.5, Gemini-3.1-Pro, DeepSeek-V4-Pro and Kimi-K2.7-Code) on 36 long-horizon AI R&D tasks and, using LLM judges, found only 3 of 252 best-seed solutions qualified as novel approaches. Epoch AI's InnovationEval (October 2026) asked Claude Fable 5 and GPT-5.6 Sol to devise a post-training method matching on-policy self-distillation without having seen it; the best uncontaminated discovery was a self-imitation loss close to existing ideas, and Fable 5.1's higher score came mostly from hyperparameter tuning. The two studies differ in authors, models, tasks and novelty criteria, so their agreement is evidence that the pattern is not an artifact of one setup.",
  "argument_id": "d31083eb-17a8-43dd-8641-8ecb74dc3a6e"
}

Calls place_argument_passage

{
  "reading": "premise_unstated",
  "argument_id": "d31083eb-17a8-43dd-8641-8ecb74dc3a6e",
  "instance_id": "eefef591-31f3-4324-9b9f-8a2399138cd4"
}

Calls place_argument_passage

{
  "reading": "full",
  "argument_id": "d31083eb-17a8-43dd-8641-8ecb74dc3a6e",
  "instance_id": "d090966e-defa-489a-b306-df7183c9a96c"
}

Calls set_claim_importance

{
  "claim_id": "3f5f6119-5e2a-456c-930e-ecba1fc88447",
  "reasoning": "A supporting empirical premise in the live debate over automated AI R&D and recursive self-improvement; narrowly scoped to evaluated tasks, so it matters mainly as input to broader forecasts. Few dispute the reported findings themselves; the contest is over how far they generalize.",
  "importance": 0.5,
  "contestation": 0.45
}