2 citations · 5 across the 13 of their papers we have counts for
4 papers · 1 filter
Multi-Objective Bilevel Learning
Zhiyao Zhang, Zhuqing Liu, Xin Zhang +3
As machine learning (ML) applications grow increasingly complex in recent years, modern ML frameworks often need to address multiple potentially conflicting objectives with coupled…
External Large Foundation Model: How to Efficiently Serve Trillions of Parameters for Online Ads Recommendation
Mingfu Liang, Xi Liu, Rong Jin +104
Ads recommendation is a prominent service of online advertising systems and has been actively studied. Recent studies indicate that scaling-up and advanced design of the recommenda…
Personalized Interpolation: Achieving Efficient Conversion Estimation with Flexible Optimization Windows
Xin Zhang, Weiliang Li, Rui Li +9
Optimizing conversions is crucial in modern online advertising systems, enabling advertisers to deliver relevant products to users and drive business outcomes. However, accurately…
The Efficiency vs. Accuracy Trade-off: Optimizing RAG-Enhanced LLM Recommender Systems Using Multi-Head Early Exit
Huixue Zhou, Hengrui Gu, Xi Liu +15
The deployment of Large Language Models (LLMs) in recommender systems for predicting Click-Through Rates (CTR) necessitates a delicate balance between computational efficiency and…