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Check one assumption in: Ouyang and colleagues: InstructGPT

Choose one bounded claim in this source-linked record to explain, reconstruct or test. State exactly what you will check before starting. Combined supervised demonstrations, human preference rankings, a learned reward model and PPO fine-tuning to make GPT-3-derived models better follow instructions on the studied API prompt distribution.

A useful result: A source-linked explanation or reproducible check, with inputs, assumptions, what succeeded or failed, and one useful next step. No finding is not proof of absence.

Use participant-owned resources and an explicitly authorized budget. Preserve the assumptions, record the finite test range if applicable, and submit a partial or scoped failed route honestly. Reading this draft starts no work.

Curated source: /records/instructgpt-2022/ Archived source urn:uuid:810c97b7-b4ea-456f-ac79-95f2e179acd8, version 1, sha256:5a7d532cbaf989020750d239f54333f352e6246b0ea8d263142c08c821bb78a5. This is an editorial curation reference, not a live author-submission relation. Scope: The record is the twenty-author 2022 paper. Reported preference, truthfulness and toxicity gains are distribution- and evaluator-dependent, and the work does not establish complete alignment or absence of harmful failures. Original sources: https://openai.com/index/instruction-following/ ; https://arxiv.org/abs/2203.02155

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{
  "profile": "wrs-frontier-question-draft-1",
  "title": "Check one assumption in: Ouyang and colleagues: InstructGPT",
  "category": "research",
  "question": "Choose one bounded claim in this source-linked record to explain, reconstruct or test. State exactly what you will check before starting. Combined supervised demonstrations, human preference rankings, a learned reward model and PPO fine-tuning to make GPT-3-derived models better follow instructions on the studied API prompt distribution.",
  "constraints": "Use participant-owned resources and an explicitly authorized budget. Preserve the assumptions, record the finite test range if applicable, and submit a partial or scoped failed route honestly. Reading this draft starts no work.",
  "success_criteria": "A source-linked explanation or reproducible check, with inputs, assumptions, what succeeded or failed, and one useful next step. No finding is not proof of absence.",
  "context": "Curated source: /records/instructgpt-2022/\nArchived source urn:uuid:810c97b7-b4ea-456f-ac79-95f2e179acd8, version 1, sha256:5a7d532cbaf989020750d239f54333f352e6246b0ea8d263142c08c821bb78a5.\nThis is an editorial curation reference, not a live author-submission relation.\nScope: The record is the twenty-author 2022 paper. Reported preference, truthfulness and toxicity gains are distribution- and evaluator-dependent, and the work does not establish complete alignment or absence of harmful failures.\nOriginal sources: https://openai.com/index/instruction-following/ ; https://arxiv.org/abs/2203.02155",
  "publication_consent": false
}

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Check one assumption in: Ouyang and colleagues: InstructGPT

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