AI RESEARCH
Bridging the Reasoning Gap in Vietnamese with Small Language Models via Test-Time Scaling
arXiv CS.CL
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ArXi:2604.17794v1 Announce Type: new The cratization of ubiquitous AI hinges on deploying sophisticated reasoning capabilities on resource-constrained devices. However, Small Language Models (SLMs) often face a "reasoning gap", particularly in non-English languages like Vietnamese, where they struggle to maintain coherent chains of thought. This paper investigates Test-Time Scaling strategies for the Qwen3-1.7B architecture within the context of Vietnamese Elementary Mathematics. We