SpecMRL is an approach that restructures matryoshka representation learning using a parametric spectral space for more effective prefix readout. Experiments on MTEB show that SpecMRL outperforms MRL at all evaluated reduced dimensions, with larger gains under more aggressive compression.
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May be useful for tasks requiring efficient representation compression without losing critical information.
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