2 papers
cs.IR2026
GRACE: Generative Recommender Acceleration Engine for Real-Time Ads Retrieval
Zhou Fang, Yuhang Huang, Ang Zhang +12
Productionizing generative recommenders for high-volume, real-time ads retrieval creates two serving challenges: eligibility, ensuring that each generated ad is eligible for the re…
cs.LG2026
KernelEvolve: Scaling Agentic Kernel Coding for Heterogeneous AI Accelerators at Meta
Gang Liao, Hongsen Qin, Ying Wang +36
Making deep learning recommendation model (DLRM) training and inference fast and efficient is important. However, this presents three key system challenges - model architecture div…