AI RESEARCH
Long-Context Aware Upcycling: A New Frontier for Hybrid LLM Scaling
arXiv CS.LG
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ArXi:2604.24715v1 Announce Type: cross Hybrid sequence models that combine efficient Transformer components with linear sequence modeling blocks are a promising alternative to pure Transformers, but most are still pretrained from scratch and. therefore. fail to reuse existing Transformer checkpoints. We study upcycling as a practical path to convert pretrained Transformer LLMs into hybrid architectures while preserving short-context quality and improving long-context capability.