{
  "id": 10468,
  "url": "https://arxiv.org/abs/2607.12631v1",
  "title": "Can Induced Emotion Bias LLM Behaviors in Sequential Decision Making?",
  "summary": "As Large Language Models (LLMs) are increasingly deployed as autonomous agents in high-stakes domains, understanding contextual factors that may modulate their decision-making becomes critical. While LLMs are trained to perceive and resonate with users' emotions, it remains unclear whether induced emotion can influence their sequential decision-making. We investigate this question using the Iowa Gambling Task (IGT), a classic psychological paradigm for studying decision-making under uncertainty,",
  "authors": "Minh Khoi Ho, Zihao Zhu, Runchuan Zhu, Levina Li, Zhiwen Fan, Zhangyang Wang, Junyuan Hong",
  "category": "research",
  "topics": "bias-fairness,agents-autonomy,finance-investment",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-14T11:09:51.000Z",
  "fetched_at": "2026-07-15T05:10:55.633Z",
  "source_slug": "x-arxiv-cs-ai",
  "source_name": "arXiv cs.AI",
  "source_homepage": "https://arxiv.org/list/cs.AI/recent",
  "ethics_ai_record_url": "https://ethics.ai/record/10468",
  "original_url": "https://arxiv.org/abs/2607.12631v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}