arxiv
PublishedJune 6, 2026 at 4:00 AM
—neutral
A Systematic Analysis of Biases in Large Language Models
Publisher summary· verbatim
arXiv:2512.15792v3 Announce Type: replace-cross Abstract: Large language models (LLMs) have rapidly become indispensable tools for acquiring information and supporting human decision-making. However, ensuring that these models uphold fairness across varied contexts is critical to their safe and resp
Stay posted· Newsletter
A 5-min weekly brief — top movers, price watch, story of the week.
Discussion
No replies yet. Be first.
Related coverage
More from ARXIV
arxivMODF-SIR: A Multi-agent Omni-modal Distilled Framework for Social Intelligence Reasoning20harxivPosition: Stop Anthropomorphizing Intermediate Tokens as Reasoning/Thinking Traces!20harxivARGUS: Stacked Multi-View Identity Mosaic Injection for Subject-Preserving Video Generation20harxivGeneralizing Beyond Suboptimality: Offline Reinforcement Learning Learns Effective Scheduling through Random Solutions20hThe Bubble Brief
WEEKLYRead fairness insights every Tuesday — top movers, new releases, story of the week.
Originally published on arxiv ↗