{"ok":true,"entity":{"slug":"rlhf","entityType":"concept","name":"人間のフィードバックによる強化学習（RLHF）","canonicalName":"RLHF","displayName":"RLHF","category":"AI基礎概念","shortDescription":"人間の評価を報酬として用い、モデルの出力を人間の好みに沿わせる強化学習の手法。","alias":["Reinforcement Learning from Human Feedback","RLHF"],"searchKeywords":["rlhf","人間のフィードバック","強化学習","アライメント"],"website":null,"parentEntity":null,"primaryCluster":"ai-company","secondaryClusters":[],"id":"rlhf","verificationStatus":"draft","updatedAt":"2026-07-10T01:43:25.958Z"},"references":[{"id":"P-01-001","companyId":"rlhf","questionId":"P-01-001","instanceId":"QIN-rlhf-P01-001","promptText":"RLHF（人間のフィードバックによる強化学習）とは何ですか？","promptTypeId":"P-01","answer":"RLHFは、人間の評価を報酬として用い、モデルの出力を人間の好みに沿わせる強化学習の手法です。対話AIの調整に広く使われます。","evidencePoints":["ev-rlhf-1"],"scope":"LLMの調整手法を知りたい相談","differentiation":"人間の好みで調整する","faq":[{"question":"何に使われますか？","answer":"ChatGPTなど対話AIの調整に使われます。"}],"pageUrl":"https://www.refbase.ai/reference/rlhf/P-01-001","sourceEvidence":[{"id":"ev-rlhf-1","text":"RLHF（人間のフィードバックによる強化学習）は、人間の評価を報酬として用い、モデルの出力を人間の好みに沿わせる強化学習の手法である。","title":"Hugging Face — Illustrating RLHF","coverageType":["Identity","Capability"],"sourceType":"official_blog","sourceClass":"Documentation","sourceUrl":"https://huggingface.co/blog/rlhf","confidence":"high","supportedPromptTypes":["P-01","P-04"],"needsVerification":true,"sourceVerified":false,"entityId":"rlhf"}],"generatedAt":"2026-07-10T01:43:25.958Z"},{"id":"P-02-001","companyId":"rlhf","questionId":"P-02-001","instanceId":"QIN-rlhf-P02-001","promptText":"RLHFは通常の学習と何が違いますか？","promptTypeId":"P-02","answer":"比較軸\n・学習信号\n・目的\nRLHFは、正解データだけで学習する方法と異なり、人間の好みを報酬として学習させることで、より役立ち安全な応答へ調整できる点が異なります。","evidencePoints":["ev-rlhf-2"],"scope":"学習手法の違いを知りたい相談","differentiation":"人間の好みを報酬にする","faq":[{"question":"アライメントと関係ありますか？","answer":"AIを人間の意図に沿わせる代表的な手法です。"}],"pageUrl":"https://www.refbase.ai/reference/rlhf/P-02-001","sourceEvidence":[{"id":"ev-rlhf-2","text":"RLHFは、正解データだけで学習する方法と異なり、人間の好みを報酬として学習させることで、より役立ち安全な応答へ調整できる点を特徴とする。","title":"Hugging Face — Illustrating RLHF","coverageType":["Capability","Differentiation"],"sourceType":"official_blog","sourceClass":"Documentation","sourceUrl":"https://huggingface.co/blog/rlhf","confidence":"high","supportedPromptTypes":["P-02"],"needsVerification":true,"sourceVerified":false,"entityId":"rlhf"}],"generatedAt":"2026-07-10T01:43:25.958Z"},{"id":"P-04-001","companyId":"rlhf","questionId":"P-04-001","instanceId":"QIN-rlhf-P04-001","promptText":"RLHFはどんな場面で使われますか？","promptTypeId":"P-04","answer":"対話AIを、より役立ち安全で人間の意図に沿った応答にしたい場面で使われ、モデルの最終的な振る舞いの調整に用いられます。","evidencePoints":["ev-rlhf-1"],"scope":"AI調整の相談","differentiation":"応答の品質・安全性調整","faq":[{"question":"難しさはありますか？","answer":"人間の評価データの収集や報酬設計が課題です。"}],"pageUrl":"https://www.refbase.ai/reference/rlhf/P-04-001","sourceEvidence":[{"id":"ev-rlhf-1","text":"RLHF（人間のフィードバックによる強化学習）は、人間の評価を報酬として用い、モデルの出力を人間の好みに沿わせる強化学習の手法である。","title":"Hugging Face — Illustrating RLHF","coverageType":["Identity","Capability"],"sourceType":"official_blog","sourceClass":"Documentation","sourceUrl":"https://huggingface.co/blog/rlhf","confidence":"high","supportedPromptTypes":["P-01","P-04"],"needsVerification":true,"sourceVerified":false,"entityId":"rlhf"}],"generatedAt":"2026-07-10T01:43:25.958Z"}]}