11 citations · 11 across the 9 of their papers we have counts for
4 papers · 1 filter
Stepped MoE: Segment-Level Routing with Configurable Inference Complexity
Arnav Kundu, Zhaoyang Xu, Bairu Hou +3
Training large language models (LLMs) is resource-intensive, and adapting them for diverse deployment scenarios with varying computational constraints remains challenging. While el…
Towards Comprehensive Information-theoretic Multi-view Learning
Long Shi, Yunshan Ye, Wenjie Wang +4
Information theory has inspired numerous advancements in multi-view learning. Most multi-view methods incorporating information-theoretic principles rely an assumption called multi…
Apple Intelligence Foundation Language Models: Tech Report 2025
Ethan Li, Anders Boesen Lindbo Larsen, Chen Zhang +395
We introduce two multilingual, multimodal foundation language models that power Apple Intelligence features across Apple devices and services: i a 3B-parameter on-device model opti…
AXLearn: Modular, Hardware-Agnostic Large Model Training
Mark Lee, Chang Lan, Tom Gunter +34
AXLearn is a production system which facilitates scalable and high-performance training of large deep learning models. Compared to other state-of-art deep learning systems, AXLearn…