{
  "id": 7065,
  "url": "https://arxiv.org/abs/2603.18113v2",
  "title": "VC-Soup: Value-Consistency Guided Multi-Value Alignment for Large Language Models",
  "summary": "As large language models (LLMs) increasingly shape content generation, interaction, and decision-making across the Web, aligning them with human values has become a central objective in trustworthy AI. This challenge becomes even more pronounced when aligning multiple, potentially conflicting human values. Although recent approaches, such as reward reweighting, prompt-based supervised fine-tuning, and model merging, attempt to tackle multi-value alignment, they still face two major limitations: ",
  "authors": "Hefei Xu, Le Wu, Yu Wang, Min Hou, Han Wu, Zhen Zhang et al.",
  "category": "research",
  "topics": "safety-alignment,finance-investment",
  "orgs": null,
  "regions": null,
  "published_at": "2026-03-18T14:05:51.000Z",
  "fetched_at": "2026-07-14T16:32:59.162Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/7065",
  "original_url": "https://arxiv.org/abs/2603.18113v2",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}