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cs.IR2024
Fusion Matters: Learning Fusion in Deep Click-through Rate Prediction Models
Kexin Zhang, Fuyuan Lyu, Xing Tang +5
The evolution of previous Click-Through Rate (CTR) models has mainly been driven by proposing complex components, whether shallow or deep, that are adept at modeling feature intera…
cs.IR2024★ 1 cited
Mixed-Precision Embeddings for Large-Scale Recommendation Models
Shiwei Li, Zhuoqi Hu, Xing Tang +6
Embedding techniques have become essential components of large databases in the deep learning era. By encoding discrete entities, such as words, items, or graph nodes, into continu…
cs.CL2024
Collaborative Performance Prediction for Large Language Models
Qiyuan Zhang, Fuyuan Lyu, Xue Liu +1
Comprehensively understanding and accurately predicting the performance of large language models across diverse downstream tasks has emerged as a pivotal challenge in NLP research.…