{
  "id": 7599,
  "url": "https://arxiv.org/abs/2603.06264v2",
  "title": "Mind the Gap: Pitfalls of LLM Alignment with Asian Public Opinion",
  "summary": "Large Language Models (LLMs) are increasingly being deployed in multilingual, multicultural settings, yet their reliance on predominantly English-centric training data risks misalignment with the diverse cultural values of different societies. In this paper, we present a comprehensive, multilingual audit of the cultural alignment of contemporary LLMs including GPT-4o-Mini, Gemini-2.5-Flash, Llama 3.2, Mistral and Gemma 3 across India, East Asia and Southeast Asia. Our study specifically focuses ",
  "authors": "Hari Shankar, Vedanta S P, Sriharini Margapuri, Debjani Mazumder, Ponnurangam Kumaraguru, Abhijnan Chakraborty",
  "category": "research",
  "topics": "safety-alignment,transparency",
  "orgs": "google,meta,mistral",
  "regions": "india",
  "published_at": "2026-03-06T13:29:54.000Z",
  "fetched_at": "2026-07-14T16:33:21.048Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/7599",
  "original_url": "https://arxiv.org/abs/2603.06264v2",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}