AI RESEARCH
BiasBusters: Uncovering and Mitigating Tool Selection Bias in Large Language Models
arXiv CS.AI
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ArXi:2510.00307v2 Announce Type: replace Agents backed by large language models (LLMs) increasingly rely on external tools drawn from marketplaces where multiple providers offer functionally equivalent options. This raises a critical fairness concern: systematic bias in tool selection can degrade user experience and distort competition by privileging certain providers over others. We