Prefix Readout
The core mechanism of MRL, in which multiple prefix dimensions of the same representation vector are each connected to downstream task heads and jointly optimized during training, so that any prefix sub-vector can be used independently for classification or retrieval.
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SpecMRL reorganizes the feature space via a parameter-derived spectral basis, achieving more effective prefix readout.
Prefix readout is the core mechanism of MRL: during training, classification or retrieval heads are attached to the first d dimensions of the same representation vector and jointly optimized, so that any prefix can be used independently.
All Facts (2)
SpecMRL reorganizes the feature space via a parameter-derived spectral basis, achieving more effective prefix readout.
50%UnverifiedPrefix readout is the core mechanism of MRL: during training, classification or retrieval heads are attached to the first d dimensions of the same representation vector and jointly optimized, so that any prefix can be used independently.
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