Can AnyExperts' dynamic expert allocation maintain consistent accuracy improvements over dense baselines when - Assignee Research (Assignee Research, 2026)
Sparse Mixture-of-Experts (MoE) architectures enable efficient scaling of large language models through conditional computation, yet the routing mechanisms responsible for expert selection remain poorly understood. In this work, we introduce routing signatures, a vector representation summarizing expert activation patterns across layers for a given prompt, and use them to study whether MoE routing exhibits task-conditioned structure. Using OLMoE-1B-7B-0125-Instruct as an empirical testbed, we sh
Machine-generated literature synthesis.