Large-model adaptation with Tibetan text handling produces natural speech from limited data, outperforming commercial systems.
Tibstc-cot: A multi-domain instruction dataset for chain-of-thought reasoning in language models
2 Pith papers cite this work. Polarity classification is still indexing.
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A seed dataset of 89 Nigerian machinery indicators plus 94 domain-grounded CoT rows, raising domain-grounded prompts from 1/78 to 94/94 and retrieval fidelity to 84/84.
citing papers explorer
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Tibetan-TTS:Low-Resource Tibetan Speech Synthesis with Large Model Adaptation
Large-model adaptation with Tibetan text handling produces natural speech from limited data, outperforming commercial systems.
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Nigeria Machinery: A Low-Resource Industrial Dataset with a Domain-Grounded Reasoning Layer
A seed dataset of 89 Nigerian machinery indicators plus 94 domain-grounded CoT rows, raising domain-grounded prompts from 1/78 to 94/94 and retrieval fidelity to 84/84.