4 papers
Xray-Visual Models: Scaling Vision models on Industry Scale Data
Shlok Mishra, Tsung-Yu Lin, Linda Wang +24
We present Xray-Visual, a unified vision model architecture for large-scale image and video understanding trained on industry-scale social media data. Our model leverages over 15 b…
Learning to Factorize and Adapt: A Versatile Approach Toward Universal Spatio-Temporal Foundation Models
Siru Zhong, Junjie Qiu, Yangyu Wu +7
Spatio-Temporal (ST) Foundation Models (STFMs) promise cross-dataset generalization, yet joint ST pretraining is computationally expensive and grapples with the heterogeneity of do…
Collab-Overcooked: Benchmarking and Evaluating Large Language Models as Collaborative Agents
Haochen Sun, Shuwen Zhang, Lujie Niu +6
Large Language Models (LLMs) based agent systems have made great strides in real-world applications beyond traditional NLP tasks. This paper proposes a new LLM-based Multi-Agent Sy…
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…