{
  "id": 14457,
  "url": "https://arxiv.org/abs/2607.23538v1",
  "title": "Guiding Language Models to Be More Empathetic: Culturally Sensitive Mental Health Advice Generation Through Human-LLM Collaboration",
  "summary": "Despite recent advances in large language models (LLMs), their ability to generate empathetic mental health counseling responses in low-resource languages remains largely unexplored. To address this gap, we curate 625 authentic mental health cases from three complementary sources: (1) publicly available Facebook posts discussing mental health concerns, (2) transcripts from the Bangladeshi television program \"Ami Akhon Ki Korbo\", and (3) anonymized student questionnaire responses covering diverse",
  "authors": "Fatema Tuj Johora Faria, Mukaffi Bin Moin, Md. Mahfuzur Rahman, Khan Md Hasib, Jubayer Al Mahmud, M. F. Mridha",
  "category": "research",
  "topics": "healthcare,children-education",
  "orgs": "meta",
  "regions": null,
  "published_at": "2026-07-26T08:27:19.000Z",
  "fetched_at": "2026-07-29T05:10:12.205Z",
  "source_slug": "x-arxiv-cs-cl-ethics-relevant-nlp",
  "source_name": "arXiv cs.CL (ethics-relevant NLP)",
  "source_homepage": "https://arxiv.org/list/cs.CL/recent",
  "ethics_ai_record_url": "https://ethics.ai/record/14457",
  "original_url": "https://arxiv.org/abs/2607.23538v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}