4 citations · 4 across the 5 of their papers we have counts for
3 papers · 1 filter
RLAX: Large-Scale, Distributed Reinforcement Learning for Large Language Models on TPUs
Runlong Zhou, Lefan Zhang, Shang-Chen Wu +29
Reinforcement learning (RL) has emerged as the de-facto paradigm for improving the reasoning capabilities of large language models (LLMs). We have developed RLAX, a scalable RL fra…
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…