Wiki cleanup: error-doc removal, dedup merge, link normalization

10_Wiki/Topics 대규모 정리:
- 오류 캡처/미완성 stub 문서 227개 제거
- 교차폴더 중복 43클러스터 병합 (63파일 → redirect)
- 링크명 정규화: 깨진 링크 수정·redirect 직결·개념 매핑 ~2,400건
- 카테고리 MOC 6개 신규 생성
- Graph 섹션 미해결 related-keyword 링크 10,058건 제거

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

10_Wiki/Topics/AI_and_ML/DPO (Direct Preference Optimization).md

@@ -252,10 +252,10 @@ def eval_preference_accuracy(model, eval_set):
 **기본값**: DPO + LoRA (efficient) + UltraFeedback.
 
 ## 🔗 Graph
-- 부모: [[LLM-Alignment]] · [[Fine-Tuning]] · [[Preference-Learning]]
-- 변형: [[ORPO]] · [[SimPO]] · [[KTO]] · [[IPO]] · [[CPO]]
-- 응용: [[TRL]] · [[Axolotl]] · [[Unsloth]] · [[Llama]]
-- Adjacent: [[RLHF]] · [[Constitutional-AI]] · [[Best-of-N_Sampling]] · [[Credit Assignment Problem]] · [[Cross-Entropy Loss]]
+- 부모: [[Fine-Tuning]] · [[Preference-Learning]]
+- 변형: [[ORPO]] · [[SimPO]] · [[KTO]] · [[IPO]]
+- 응용: [[Axolotl]] · [[Llama]]
+- Adjacent: [[RLHF]] · [[AI_Safety_and_Alignment|Constitutional-AI]] · [[Best-of-N_Sampling]] · [[Credit Assignment Problem]] · [[Cross-Entropy Loss]]
 
 ## 🤖 LLM 활용
 **언제**: 매 LLM alignment. 매 customer-specific tone. 매 RLHF alternative. 매 fine-tune at scale.
@@ -272,7 +272,7 @@ def eval_preference_accuracy(model, eval_set):
 ## 🧪 검증 / 중복
 - Verified (Rafailov et al. 2023 DPO, ORPO 2024, KTO 2024).
 - 신뢰도 A.
-- Related: [[RLHF]] · [[Constitutional-AI]] · [[Best-of-N_Sampling]] · [[Credit Assignment Problem]] · [[Cross-Entropy Loss]].
+- Related: [[RLHF]] · [[AI_Safety_and_Alignment|Constitutional-AI]] · [[Best-of-N_Sampling]] · [[Credit Assignment Problem]] · [[Cross-Entropy Loss]].
 
 ## 🕓 Changelog
 | 날짜 | 변경 |