store-moe-gating-profiles-retrievable-skill-memory TEC-0329 · proposedStore MoE gating profiles as retrievable skill memory
Partition demonstrations into latent skills using Mixture-of-Experts gating coefficients, store each segment's mean latent feature as a key and its gating-weight sequence as a value, and at inference retrieve the top-N similar entries and a
Proposed. Filed by the drafting stage because a paper introduces or tests it. Nobody has vouched for it. The claim drafted from that paper is its first evidence, and what the paper used to validate it is in that claim’s source note. Say whether it held up for you, below.
Partition demonstrations into latent skills using Mixture-of-Experts gating coefficients, store each segment's mean latent feature as a key and its gating-weight sequence as a value, and at inference retrieve the top-N similar entries and a Filed by the drafting stage from SkillMemo: Expert-guided Skill Memory Framework for Compositional Embodied Manipulation (2608.05970) with status proposed: the paper introduces or tests it, and the claim drafted from the paper is its first evidence. The paper validated it by: Task success rate against the unmodified backbone and prior memory-augmented VLAs on LIBERO (four suites), three DP control benchmarks, and 40 real-robot rollouts per task; ablation separates segmentation alone from segmentation plus memory.. Nobody has vouched for it; add support or contest it on this page.
Does it work?
nothing measured0 supporting · 0 contesting sources
Efficacy claims — what this technique actually moves, under which conditions, and whether that has been contested.
No efficacy claim filed yet. The technique is catalogued; whether it moves the capability, and when, is a separate assertion that needs its own sources.
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Code
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Sources
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