cd /news/machine-learning/what-we-keep-of-what-we-forget-repla… · home › topics › machine-learning › article
[ARTICLE · art-163594] src=aiflash.com ↗ pub= topic=machine-learning verified=true sentiment=· neutral

What We Keep of What We Forget: Replacement Operators and Routing Semantics in Training-Free MoE Expert Pruning

A study comparing replacement operators for training-free MoE expert pruning, holding the pruning mask fixed, evaluated three operator families on OLMoE, DeepSeek-V2-Lite and Mo (a third model whose name is truncated in the source). The work isolates the second of the two decisions training-free expert pruning makes — what a layer computes when its router still selects a removed expert — since published methods change the mask and the replacement operator at once. The comparison covers OLMoE, DeepSeek-V2-Lite and Mo, but the source excerpt does not report results.

read1 min views2 publishedNov 4, 2026

Training-free expert pruning makes two decisions: which experts to remove, and what the layer computes when its router still selects a removed expert. Published methods change both at once. Holding the mask fixed, we compare replacement operators from three families on OLMoE, DeepSeek-V2-Lite and Mo

── more in #machine-learning 4 stories · sorted by recency
── more on @olmoe 3 stories trending now
sponsored brought to you by zahid.host 4,200+ EU-deployed projects
reading about agents? ship yours in a single git push.

Run your AI side-project on zahid.host

EU-based hosting, git-push deploys, automatic HTTPS, no cold starts. Free tier with a custom domain — perfect for shipping the agent you just read about.

$git push zahid main
→ Live at https://your-agent.zahid.host ✓
Get free account → Pricing
from €0/mo · no card required
LIVE [news/what-we-keep-of-what…] indexed:0 read:1min 2026-11-04 · —