Limited Stereotype Control Through Routing Reweighting in MoE Language Models
Demographic prompts are routed differently from neutral prompts in Mixture-of-Experts (MoE) language models, motivating tests of routing-level stereotype control. We introduce Fairness-Aware Routing Equilibrium (FARE), a diagnostic framework combining demographic routing profiles, empirical layer selection, and fixed inference-time reweighting, and evaluate five MoE architectures in English. At the selected operating points, CrowS-Pairs preference changes by at most 1.3 percentage points; DeepSeekMoE selects no intervention. Paired 95% confidence intervals exclude decreases larger than 2.2 points on each intervened model, and the only nominally significant change (Qwen1.5, p = 0.015) does...
| Authors | Junhyeok Lee, Han Jang, Kyu Sung Choi |
|---|---|
| Primary category | cs.CL |
| Published | 28 March 2026 |
| Last updated at source | 8 October 2026 |
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