| CPC G06F 16/2457 (2019.01) [G06F 16/2462 (2019.01)] | 20 Claims |

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1. A method comprising:
encoding a search input into a first dense vector based on a first multi-modal search model of a model store of a storage system;
determining, based on the first dense vector, a distilled data item corresponding to the search input from a distilled dataset corresponding to the first multi-modal search model, wherein the distilled dataset is generated from an original dataset utilizing a data distillation model of the model store of the storage system, the first multi-modal search model of the model store of the storage system being constructed based on the distilled dataset, and wherein the first multi-modal search model has an accuracy that is less than that of a second multi-modal search model constructed based on the original dataset;
encoding, based on the first multi-modal search model, an original data item in an original data subset corresponding to the distilled data item in the original dataset corresponding to the distilled dataset into a second dense vector; and
determining, based on the second dense vector, an original data item from the original data subset as a search result corresponding to the search input.
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