3 papers
cs.CL2026
Efficient LLM-based Advertising via Model Compression and Parallel Verification
Wenxin Dong, Chang Gao, Guanghui Yu +9
Large language models (LLMs) have shown remarkable potential in advertising scenarios such as ad creative generation and targeted advertising. However, deploying LLMs in real-time…
cs.CL2026
Ada-MK: Adaptive MegaKernel Optimization via Automated DAG-based Search for LLM Inference
Wenxin Dong, Mingqing Hu, Guanghui Yu +7
When large language models (LLMs) serve real-time inference in commercial online advertising systems, end-to-end latency must be strictly bounded to the millisecond range. Yet ever…
cs.IR2022
Communication-Efficient TeraByte-Scale Model Training Framework for Online Advertising
Weijie Zhao, Xuewu Jiao, Mingqing Hu +3
Click-Through Rate (CTR) prediction is a crucial component in the online advertising industry. In order to produce a personalized CTR prediction, an industry-level CTR prediction m…