2026
BiasBusters: Uncovering and Mitigating Tool Selection Bias in Large Language Models
ICLR 2026poster
Agents backed by large language models (LLMs) often rely on external tools drawn from marketplaces where multiple providers offer functionally equivalent options. This raises a critical point concerning fairness: if selection is systematically biased, it can degrade user experience and distort compe…