Superbloom: Bloom filter meets Transformer

Anderson John
Anderson John
Huang Qingqing
Huang Qingqing
Zhang Li
Zhang Li
Cited by: 0|Bibtex|Views66
Other Links: arxiv.org

Abstract:

We extend the idea of word pieces in natural language models to machine learning tasks on opaque ids. This is achieved by applying hash functions to map each id to multiple hash tokens in a much smaller space, similarly to a Bloom filter. We show that by applying a multi-layer Transformer to these Bloom filter digests, we are able to ob...More

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