Evidence record 16980 · automatically gathered

SpecDrop: Parameter-Free Category-Conditioned Routing for Modular Specialization

Mixture-of-experts (MoE) networks pursue specialization through learned routers, gates, and load-balancing losses, yet at matched total-parameter budgets learned routers can underperform equal-weight No-Routing baselines. Is the bottleneck the routing algorithm, or the alignment between training-signal granularity and the target categories? We probe the question with SpecDrop, a fixed parameter-free routing scheme: each of $K$ branches receives weight $p_a$ for its assigned category and a small

Record details

Published: 4 August 2026
Source: arXiv cs.LG
Category: Research
Topics: Safety & alignment
Retrieved: 6 August 2026

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ethics.ai (4 August 2026), “SpecDrop: Parameter-Free Category-Conditioned Routing for Modular Specialization,” evidence record 16980, https://ethics.ai/record/16980 (originally published by arXiv cs.LG).

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