Improving Reasoning Efficiency: While maintaining high reasoning quality, improving reasoning efficiency is another critical challenge. Efficient reasoning directly impacts the model's practicality and cost-effectiveness in real-world applications. Approaches such as knowledge distillation (transferring knowledge from complex models to smaller models) can be explored to reduce computational resource consumption, or the use of Long Chain-of-Thought (Long-CoT) techniques to improve Short-CoT models to balance reasoning accuracy with computational efficiency.
Got PhD degree in Computer Science, Electronics, or other related fields.
Extensive experience in ML/CV/NLP/Recommendation Systems, including but not limited to:
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Draft and maintain communication materials, process guides, FAQs, and policy-related resources to improve clarity, consistency, and user experience.
Contribute to the development, implementation, and continuous improvement of immigration policies, processes, and operational frameworks.
Analyse case trends, operational metrics, and stakeholder feedback to identify insights, support decision-making, and recommend process improvements.
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