Is MoE-LLaVA superseded?

MoE-LLaVA (Mixture-of-experts routing): superseded — cited as a baseline and beaten by newer methods. 0 paper(s) critique it, 3 beat it on benchmarks — #19 of 1370 most-superseded. Sub-problem: cluster led by MoE-LLaVA. Newer alternatives in the same sub-problem include MoE-GRPO, Input Domain Aware MoE.

Mixture-of-experts routing

MoE-LLaVA

MoE-LLaVA: Mixture of Experts for Large Vision-Language Models

Superseded baseline#19 of 1,370 most-superseded · first seen Jan 29, 2024

Superseded — cited as a baseline and beaten by newer methods

0 papers critique it · 3 beat it on benchmarks

Beaten on benchmarks

Head-to-head results where a newer method reports beating MoE-LLaVA. Values are copied from the source paper's tables — verify against the cited paper.

IDA-MoE beats MoE-LLaVA
43.1 vs 36.2
VizWiz · [StableLM-1.6B + CLIP-336]
Input Domain Aware MoE: Decoupling Routing Decisions from Task Optimization in Mixture of Experts
EvoMoE beats MoE-LLaVA
67.0 vs 65.9
AVG · [1-2B Sparse Model (S-1.6B)]
EvoMoE: Expert Evolution in Mixture of Experts for Multimodal Large Language Models

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Recent methods in the same sub-problem, not yet superseded in the knowledge base — arXiv benchmark leaders, not vetted production recommendations.

MoE-GRPOMoE-GRPO: Optimizing Mixture-of-Experts via Reinforcement Learning in Vision-Language Models
Mar 26, 2026
Input Domain Aware MoEInput Domain Aware MoE: Decoupling Routing Decisions from Task Optimization in Mixture of Experts
Oct 18, 2025