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cs.IR2024
Learning Deep Tree-based Retriever for Efficient Recommendation: Theory and Method
Ze Liu, Jin Zhang, Chao Feng +3
Although advancements in deep learning have significantly enhanced the recommendation accuracy of deep recommendation models, these methods still suffer from low recommendation eff…
cs.IR2023★ 2 cited
NineRec: A Benchmark Dataset Suite for Evaluating Transferable Recommendation
Jiaqi Zhang, Yu Cheng, Yongxin Ni +6
Large foundational models, through upstream pre-training and downstream fine-tuning, have achieved immense success in the broad AI community due to improved model performance and s…