Challenge: Existing user modeling benchmarks focus on short sessions and next-item prediction within a single domain.
Approach: They propose a benchmark that reformulates user modeling along three axes . it covers 54M users and 35M items, enabling pretraining and evaluation . they propose tasks and evaluation setups that better reflect real-world deployment scenarios .
Outcome: The proposed benchmark covers 54M users and 35M items, and is based on Amazon Reviews.

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