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cs.CL2026
Mixture of Training: Recombining Small-Scale Scaffolded Pretraining Runs into a Larger Language Model
Mohammed Sabry, Sean Augenstein, Keith Rush +1
We ask whether language-model pre-training can be decomposed into smaller, independently trainable jobs that can later be recomposed into a coherent larger model. We introduce Mixt…
cs.CL2026
Decoupled DiLoCo for Resilient Distributed Pre-training
Arthur Douillard, Keith Rush, Yani Donchev +14
Modern large-scale language model pre-training relies heavily on the single program multiple data (SPMD) paradigm, which requires tight coupling across accelerators. Due to this co…
cs.CL2025
Streaming DiLoCo with overlapping communication: Towards a Distributed Free Lunch
Arthur Douillard, Yanislav Donchev, Keith Rush +11
Training of large language models (LLMs) is typically distributed across a large number of accelerators to reduce training time. Since internal states and parameter gradients need…