{
  "id": 7017,
  "url": "https://arxiv.org/abs/2603.18729v1",
  "title": "Analysis Of Linguistic Stereotypes in Single and Multi-Agent Generative AI Architectures",
  "summary": "Many works in the literature show that LLM outputs exhibit discriminatory behaviour, triggering stereotype-based inferences based on the dialect in which the inputs are written. This bias has been shown to be particularly pronounced when the same inputs are provided to LLMs in Standard American English (SAE) and African-American English (AAE). In this paper, we replicate existing analyses of dialect-sensitive stereotype generation in LLM outputs and investigate the effects of mitigation strategi",
  "authors": "Martina Ullasci, Marco Rondina, Riccardo Coppola, Flavio Giobergia, Riccardo Bellanca, Gabriele Mancari Pasi et al.",
  "category": "research",
  "topics": "bias-fairness,agents-autonomy,finance-investment",
  "orgs": null,
  "regions": "us,africa",
  "published_at": "2026-03-19T10:24:51.000Z",
  "fetched_at": "2026-07-14T16:32:54.534Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/7017",
  "original_url": "https://arxiv.org/abs/2603.18729v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}