LoopRec assigns per-item recursion depth in sequential recommenders
A shared block and per-item exit gate beat matched fixed-depth models; rarer and more recent items get deeper compute.
2 stories, newest first · one card per story
A shared block and per-item exit gate beat matched fixed-depth models; rarer and more recent items get deeper compute.
RLCP adapts sequential-recommendation action sets with calibrated pruning, lifting catalog diversity to 1.11–5.21× the best baselines.
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