Is EvoESAP superseded?

EvoESAP (Mixture-of-experts routing): current frontier — recent, not yet superseded in the knowledge base. 0 paper(s) critique it, 0 beat it on benchmarks — not ranked as a superseded baseline.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 MC-SMoE. Newer alternatives in the same sub-problem include Less is MoE, TIDE, CoX-MoE, HodgeCover, Temporally Extended Mixture-of-Experts.

Mixture-of-experts routing

EvoESAP

EvoESAP: Non-Uniform Expert Pruning for Sparse MoE

On the frontierfirst seen Mar 6, 2026

Current frontier — recent, not yet superseded in the knowledge base

0 papers critique it · 0 beat it on benchmarks

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Recent methods in the same sub-problem, not yet superseded in the knowledge base — arXiv benchmark leaders, not vetted production recommendations.

Less is MoELess is MoE: Trimming Experts in Domain-Specialist Language Models
Jun 4, 2026
TIDETIDE: Efficient and Lossless MoE Diffusion LLM Inference with I/O-aware Expert Offload
May 19, 2026
CoX-MoECoX-MoE: Coalesced Expert Execution for High-Throughput MoE Inference with AMX-Enabled CPU-GPU Co-Execution
May 18, 2026
HodgeCoverHodgeCover: Higher-Order Topological Coverage Drives Compression of Sparse Mixture-of-Experts
May 13, 2026
Temporally Extended Mixture-of-ExpertsTemporally Extended Mixture-of-Experts Models
Apr 22, 2026
MoEITSMoEITS: A Green AI approach for simplifying MoE-LLMs
Apr 12, 2026
Alloc-MoEAlloc-MoE: Budget-Aware Expert Activation Allocation for Efficient Mixture-of-Experts Inference
Apr 9, 2026
AIMERAIMER: Calibration-Free Task-Agnostic MoE Pruning
Mar 19, 2026
LightMoELightMoE: Reducing Mixture-of-Experts Redundancy through Expert Replacing
Mar 13, 2026
SliceMoESliceMoE: Bit-Sliced Expert Caching under Miss-Rate Constraints for Efficient MoE Inference
Mar 12, 2026
EvoESAPEvoESAP: Non-Uniform Expert Pruning for Sparse MoE
Mar 6, 2026