From the 1 of 10 linked papers with an AI index.
4 papers · 1 filter
MARCO: Click-Intent Decomposition for Calibrated Ads Conversion Prediction
Shiwen Shen, Xiru Huang, Liang Luo +32
Not all clicks are equal. Industrial ads ranking decouples conversion probability into click-through rate (CTR) and post-click conversion rate (CVR), yet treats every click as the…
ROCS: Request-Oriented Compute Sharing for Efficient Large-Scale Recommendation
Yuxin Chen, Liang Luo, Buyun Zhang +44
The paper introduces ROCS, a request-oriented compute sharing framework that restructures recommendation inference to evaluate shared request features once per request rather than…
LoKA: Low-precision Kernel Applications for Recommendation Models At Scale
Liang Luo, Yinbin Ma, Quanyu Zhu +21
Recent GPU generations deliver significantly higher FLOPs using lower-precision arithmetic, such as FP8. While successfully applied to large language models (LLMs), its adoption in…
LoopFM: Learning frOm HistOrical RePresentations of Foundation Model for Recommendation
Shali Jiang, Hua Zheng, Boyang Liu +40
Knowledge distillation (KD) transfers a single scalar prediction from a large foundation model (FM) to compact vertical models (VMs), suffering from diminishing transfer ratio -- t…