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Shanghai Jiao Tong University
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Allocating rollout budgets based on state informativeness allows LLM agents to achieve superior performance in complex decision-making tasks without increasing computational costs.
Speech-driven features can dramatically enhance the accuracy of language discrimination among Chinese dialects, surpassing traditional text-based approaches.
Achieving superior performance in Chinese dialect discrimination by effectively combining transfer learning with innovative data augmentation techniques could redefine benchmarks in low-resource NLP tasks.