Step 15: assistant

thinking

Calls update_claim_instance

{
  "context": "Abstract and introduction of a systematic evaluation of seven frontier models on 36 long-horizon AI R&D tasks; the introduction adds that only three of 252 best-seed solutions qualified as novel under an LLM-judge review protocol.",
  "speaker": "Yiwei Li et al.",
  "claim_id": "3f5f6119-5e2a-456c-930e-ecba1fc88447",
  "reasoning": "Read the abstract and introduction; the passage states the claim almost verbatim, so confidence raised and speaker/date filled.",
  "confidence": 0.95,
  "instance_id": "c79ec5d5-2231-4d01-95e8-5eb9b49f1e64",
  "source_date": "2026-08-13"
}

Calls update_claim_instance

{
  "speaker": "David Owen (Epoch AI)",
  "claim_id": "3f5f6119-5e2a-456c-930e-ecba1fc88447",
  "reasoning": "The recorded passage was about lack of progress on metrics, not about novelty of solutions; replaced with the passage that states the claim's content directly.",
  "instance_id": "2434175c-ba28-40ab-ad1e-462a385ad6ae",
  "source_date": "2026-10-07",
  "verbatim_text": "Here, the most noteworthy discovery from an uncontaminated model was GPT-5.6 Sol’s use of a self-imitation loss in a GRPO setting to derive signal from all-pass groups. Given its similarity to pre-existing ideas and weak performance, this would struggle to clear the bar of Moderately Interesting. Although Fable 5.1 scored higher, it also relied on straightforward applications of existing techniques, and would also struggle to clear the bar."
}