Register Bias in Complexity-Based Large Language Model Routing
Complexity-based routing in multi-model systems may introduce unintended performance disparities and systemic bias.
Large language model services increasingly route each query to one of several models of differing capability, using a cheap estimate of query complexity to send easy queries to small models and hard queries to large ones. I show that this routing step is not register neutral: tex...
ArXiv CS.CL
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Routing mechanisms that prioritize computational efficiency can inadvertently create systemic bias by funneling specific types of queries into lower-performing models. This research highlights a critical vulnerability where cost-optimization strategies compromise the equitable and accurate performance of distributed AI architectures.
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