3 papers
cs.IR2025
DashCLIP: Leveraging multimodal models for generating semantic embeddings for DoorDash
Omkar Gurjar, Kin Sum Liu, Praveen Kolli +2
Despite the success of vision-language models in various generative tasks, obtaining high-quality semantic representations for products and user intents is still challenging due to…
cs.GT2025
Smart Fast Finish: Preventing Overdelivery via Daily Budget Pacing at DoorDash
Rohan Garg, Yongjin Xiao, Jason +2
We present a budget pacing feature called Smart Fast Finish (SFF). SFF builds upon the industry standard Fast Finish (FF) feature in budget pacing systems that depletes remaining a…
cs.LG2025
Applying Deep Learning to Ads Conversion Prediction in Last Mile Delivery Marketplace
Di Li, Xiaochang Miao, Huiyu Song +3
Deep neural networks (DNNs) have revolutionized web-scale ranking systems, enabling breakthroughs in capturing complex user behaviors and driving performance gains. At DoorDash, we…