MONA integrates Nesterov acceleration into Muon's orthogonalization framework, reporting better convergence than Muon and AdamW on MoE models up to 68B parameters trained on 1T tokens and SOTA fine-tuning results.
Shortcut-connected expert parallelism for accelerating mixture-of-experts
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Chameleon provides adaptive fault tolerance for distributed training by real-time selection of optimal recovery policies via a unified performance model, demonstrated with low overhead on a 32-card cluster.
A systematic literature review that organizes recent work on LLMs for code generation into a taxonomy covering data curation, model advances, evaluations, ethics, environmental impact, and applications, with benchmark comparisons.
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A Survey on Large Language Models for Code Generation
A systematic literature review that organizes recent work on LLMs for code generation into a taxonomy covering data curation, model advances, evaluations, ethics, environmental impact, and applications, with benchmark comparisons.
- MACS: Modality-Aware Capacity Scaling for Efficient Multimodal MoE Inference