Mixture-of-experts routing
AdaMoE
AdaMoE: Token-Adaptive Routing with Null Experts for Mixture-of-Experts Language Models
Superseded baseline#74 of 1,370 most-superseded · first seen Jun 19, 2024
Superseded — cited as a baseline and beaten by newer methods
0 papers critique it · 2 beat it on benchmarks
Beaten on benchmarks
Head-to-head results where a newer method reports beating AdaMoE. Values are copied from the source paper's tables — verify against the cited paper.
ZEDA beats AdaMoE
74.2 vs 54.8
Avg Acc · [Qwen3-30B-A3B]
Post-Trained MoE Can Skip Half Experts via Self-DistillationEMoE beats AdaMoE
45.68 vs 41.34
AVG · [EMoE vs AdaMoE, k'=1.3]
Elastic MoE: Unlocking the Inference-Time Scalability of Mixture-of-Experts
What to use instead
Recent methods in the same sub-problem, not yet superseded in the knowledge base — arXiv benchmark leaders, not vetted production recommendations.
- Jun 1, 2026
- May 18, 2026
- Feb 17, 2026
- Mixture-of-Experts (MoE) AdaptationUnderstanding and Harnessing Sparsity in Unified Multimodal ModelsDec 2, 2025
- Elastic Mixture-of-Experts (EMoE)Elastic MoE: Unlocking the Inference-Time Scalability of Mixture-of-ExpertsSep 26, 2025