1 citations · 1 across the 3 of their papers we have counts for
4 papers
FreeScale: Distributed Training for Sequence Recommendation Models with Minimal Scaling Cost
Chenhao Feng, Haoli Zhang, Shakhzod Ali-Zade +17
Modern industrial Deep Learning Recommendation Models typically extract user preferences through the analysis of sequential interaction histories, subsequently generating predictio…
The Llama 4 Herd: Architecture, Training, Evaluation, and Deployment Notes
Redacted by arXiv
This document consolidates publicly reported technical details about Metas Llama 4 model family. It summarizes (i) released variants (Scout and Maverick) and the broader herd conte…
Scaling Generative Recommendations with Context Parallelism on Hierarchical Sequential Transducers
Yue Dong, Han Li, Shen Li +4
Large-scale recommendation systems are pivotal to process an immense volume of daily user interactions, requiring the effective modeling of high cardinality and heterogeneous featu…
Face Recognition with Hybrid Efficient Convolution Algorithms on FPGAs
Chuanhao Zhuge, Xinheng Liu, Xiaofan Zhang +3
Deep Convolutional Neural Networks have become a Swiss knife in solving critical artificial intelligence tasks. However, deploying deep CNN models for latency-critical tasks remain…