Speculating Experts Accelerates Inference for Mixture-of-Experts
arXiv 2603.19289•7d8307a1f8542ab5fe4c66d070a0e075814b7da15c350177bd98099234c8c3d4
CLaREDBML-SALLM-inferenceMIPOPRIME-CVDSTEUTTQclinical-mlcontrastive-learningmachine-unlearningmedical-privacymixture-of-expertsmodel-editingmodel-personalizationmutual-informationoffloadoperator-situation-awarenessperformance-optimizationprivacyrepresentation-entanglementsafety-critical-systemsspeculative-prefetchingsynthetic-datatest-time-quantization
Paper metadata
- arXiv ID
- 2603.19289
- Version
- Not specified by this published record
- Category
- Computer Science — Machine Learning (cs.LG)
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Evidence and limitations
- Source ID
- arxiv_cs_lg
- Record identifier
- 7d8307a1f8542ab5fe4c66d070a0e075814b7da15c350177bd98099234c8c3d4
- Enrichment time
- 2026-03-23T08:52:24Z
- AI-assisted enrichment
- Yes
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