mlsanityData to 14 Oct 2026

Korean Culture into LLM Alignment: Toward Cultural Coherence

arXiv 2606.06797 ↗First posted 5 Jun 2026cs.CLcited by 2

On the map: LLM alignment / RLHF / preference optimisation → Human values and AI feedback alignment

Abstract (arXiv)

Cultural-aspect work on large language models is dominated by a negative target: which outputs to suppress. We argue that a constructive counterpart is also needed, a working definition of what a culturally coherent response is rather than only what it must avoid, and instantiate it for Korean. We design an alignment-data pipeline around a prompt-based LLM seed generator that expands a Korean harm taxonomy, with a Korean-culturally-adapted safe-response policy at its centre: a per-category guideline grounded in Korean legal frameworks, social norms, and interpretive conventions, against which three frontier models each produce a candidate response. DPO fine-tuning on the resulting triplets improves the Korean cultural safe rate across six open-weight LLMs while causing no large degradation on Korean general-capability benchmarks, and qualitative outputs show fine-tuned models naming Korean statutes and institutional procedures and, where appropriate, supplying constructive Korean-context information alongside refusal.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Placed in Human values and AI feedback alignment, one of 10 directions in LLM alignment / RLHF / preference optimisation. Builds on 17 of its 24 references that are in the map. First posted on arXiv 5 Jun 2026.

Builds on

17 of 24 references.

Closest ancestors · 2

Same direction, newest first

  1. 2024KorNAT: LLM Alignment Benchmark for Korean Social Values and Common Knowledge21 Feb
  2. 2023Cultural Bias and Cultural Alignment of Large Language Models23 Nov

Other references · 15

  1. 2023Judging LLM-as-a-Judge with MT-Bench and Chatbot Arenacited by 8,626
  2. 2023Direct Preference Optimization: Your Language Model is Secretly a Reward Modelcited by 8,065
  3. 2022Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedbackcited by 3,720
  4. 2023Jailbroken: How Does LLM Safety Training Fail?cited by 1,651
  5. 2023Is Your Code Generated by ChatGPT Really Correct? Rigorous Evaluation of Large Language Models for Code Generationcited by 1,391
  6. 2023XSTest: A Test Suite for Identifying Exaggerated Safety Behaviours in Large Language Modelscited by 505
  7. 2024OR-Bench: An Over-Refusal Benchmark for Large Language Modelscited by 244
  8. 2025X-Teaming: Multi-Turn Jailbreaks and Defenses with Adaptive Multi-Agentscited by 125
  9. 2024KMMLU: Measuring Massive Multitask Language Understanding in Koreancited by 91
  10. 2023KoBBQ: Korean Bias Benchmark for Question Answeringcited by 71
  11. 2024EXAONE 3.5: Series of Large Language Models for Real-world Use Casescited by 53
  12. 2025Understand, Solve and Translate: Bridging the Multilingual Mathematical Reasoning Gapcited by 43
3 more
  1. 2024EXAONE 3.0 7.8B Instruction Tuned Language Modelcited by 21
  2. 2026CAGE: A Framework for Culturally Adaptive Red-Teaming Benchmark Generationcited by 3
  3. 2026STAR-Teaming: A Strategy-Response Multiplex Network Approach to Automated LLM Red Teamingcited by 2

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 2.

2 papers.

Similar, not cited

Close in wording, no citation either way

  1. 2024Navigating the Cultural Kaleidoscope: A Hitchhiker's Guide to Sensitivity in Large Language Models
  2. 2025Randomness, Not Representation: The Unreliability of Evaluating Cultural Alignment in LLMs
  3. 2025Nunchi-Bench: Benchmarking Language Models on Cultural Reasoning with a Focus on Korean Superstition
  4. 2023CDEval: A Benchmark for Measuring the Cultural Dimensions of Large Language Models
  5. 2025Break the Checkbox: Challenging Closed-Style Evaluations of Cultural Alignment in LLMs
  6. 2024Developing a Pragmatic Benchmark for Assessing Korean Legal Language Understanding in Large Language Models
  7. 2025CURE: Cultural Understanding and Reasoning Evaluation - A Framework for "Thick" Culture Alignment Evaluation in LLMs
  8. 2023HAE-RAE Bench: Evaluation of Korean Knowledge in Language Models