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cs.LG2023
Rethinking Memory and Communication Cost for Efficient Large Language Model Training
Chan Wu, Hanxiao Zhang, Lin Ju +8
Recently, various distributed strategies for large language model training have been proposed. However, these methods provided limited solutions for the trade-off between memory co…
cs.IR2023★ 2 cited
One Model for All: Large Language Models are Domain-Agnostic Recommendation Systems
Zuoli Tang, Zhaoxin Huan, Zihao Li +6
Sequential recommendation systems aim to predict users' next likely interaction based on their history. However, these systems face data sparsity and cold-start problems. Utilizing…
cs.IR2023
AntMC: A Large Scale Dataset For Multi-Scenario Multi-Modal CTR Prediction
Zhaoxin Huan, Ke Ding, Ang Li +10
Click-through rate (CTR) prediction is a crucial issue in recommendation systems. There has been an emergence of various public CTR datasets. However, existing datasets primarily s…