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Multi-Embedding (ICML 2024)

On the Embedding Collapse When Scaling Up Recommendation Models [paper]

Recommendation models lack scalability due to the embedding collapse phenomenon. We propose multi-embedding to overcome embedding collapse while maintaining feature interactions modules.

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About Code Release for "On the Embedding Collapse When Scaling Up Recommendation Models" (ICML 2024)

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