Bridging the Reasoning Gap in Vietnamese with Small Language Models via Test-Time Scaling explores This paper demonstrates that Test-Time Scaling and Supervised Fine-Tuning can bridge the reasoning gap in Vietnamese Small Language Models, outperforming complex agentic workflows for edge deployment.. Commercial viability score: 7/10 in Small Language Models.
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Canonical route: /paper/bridging-the-reasoning-gap-in-vietnamese-with-small-language-models-via-test-time-scaling
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Canonical ID bridging-the-reasoning-gap-in-vietnamese-with-small-language-models-via-test-time-scaling | Route /paper/bridging-the-reasoning-gap-in-vietnamese-with-small-language-models-via-test-time-scaling
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/paper/bridging-the-reasoning-gap-in-vietnamese-with-small-language-models-via-test-time-scalingMCP example
{
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}source_context
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}Constellation, claims, and market context stay visible on the paper proof page even when commercialization rails are held back for incomplete proof receipts.
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