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MultiSlot ReRanker: A Generic Model-based Re-Ranking Framework in Recommendation Systems
In this paper, we propose a generic model-based re-ranking framework, MultiSlot ReRanker, which simultaneously optimizes relevance, diversity, and freshness.
FFSplit: Split Feed-Forward Network For Optimizing Accuracy-Efficiency Trade-off in Language Model Inference
This usually results in a trade-off between model accuracy and efficiency.
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