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cs.IR2026
MALLOC: Benchmarking the Memory-aware Long Sequence Compression for Large Sequential Recommendation
Qihang Yu, Kairui Fu, Zhaocheng Du +10
The scaling law, which indicates that model performance improves with increasing dataset and model capacity, has fueled a growing trend in expanding recommendation models in both i…
cs.IR2023★ 1 cited
DCMT: A Direct Entire-Space Causal Multi-Task Framework for Post-Click Conversion Estimation
Feng Zhu, Mingjie Zhong, Xinxing Yang +8
In recommendation scenarios, there are two long-standing challenges, i.e., selection bias and data sparsity, which lead to a significant drop in prediction accuracy for both Click-…