Kin Meng Ng

Adapting Hybrid Parallel-Head Large Language Models for Southeast Asia

Large language models (LLMs) have rapidly advanced, but their growing compute demands limit accessibility in under-resourced regions like Southeast Asia (SEA). While hybrid architectures combining Attention and State-Space Models (SSMs) offer efficiency gains, most rely on sequential interleaving, l