Is SR-MoE superseded?

SR-MoE (Mixture-of-experts routing): current frontier — recent, not yet superseded in the knowledge base. 0 paper(s) critique it, 0 beat it on benchmarks — not ranked as a superseded baseline. Sub-problem: cluster led by ReMoE. Newer alternatives in the same sub-problem include ProbMoE, Grouter, DECO, AIR-MoE, SPHERE.

Method Drift›Mixture-of-experts routing

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SR-MoE

Spectral Manifold Regularization for Stable and Modular Routing in Deep MoE Architectures

Mixture-of-experts routing · first seen Jan 7, 2026

current frontier — recent, not yet superseded in the knowledge base

0 papers critique it · 0 beat it on benchmarks

Newer alternatives

Recent methods in the same sub-problem, not yet superseded in the knowledge base.

ProbMoE ProbMoE: Differentiable Probabilistic Routing for Mixture-of-Experts
Jun 1, 2026
Grouter Grouter: Decoupling Routing from Representation for Accelerated MoE Training
May 24, 2026
DECO DECO: Sparse Mixture-of-Experts with Dense-Comparable Performance on End-Side Devices
May 11, 2026
AIR-MoE Adaptive Inverted-Index Routing for Granular Mixtures-of-Experts
May 6, 2026
SPHERE SPHERE: Mitigating the Loss of Spectral Plasticity in Mixture-of-Experts for Deep Reinforcement Learning
May 6, 2026
bias-driven sparsification with always-active gated condenser experts Preserving Long-Tailed Expert Information in Mixture-of-Experts Tuning
Apr 24, 2026
TGR-MoE Teacher-Guided Routing for Sparse Vision Mixture-of-Experts
Apr 23, 2026
MalMoE MalMoE: Mixture-of-Experts Enhanced Encrypted Malicious Traffic Detection Under Graph Drift
Feb 10, 2026
DirMoE DirMoE: Dirichlet-routed Mixture of Experts
Feb 9, 2026
OmniMoE OmniMoE: An Efficient MoE by Orchestrating Atomic Experts at Scale
Feb 5, 2026
GRIP (Geometric Routing Invariance Preservation)GRIP: Algorithm-Agnostic Machine Unlearning for Mixture-of-Experts via Geometric Router Constraints
Jan 23, 2026
SR-MoE Spectral Manifold Regularization for Stable and Modular Routing in Deep MoE Architectures
Jan 7, 2026