Explore the application and implementation of cutting-edge research such as large language models, graph neural networks, and multimodal techniques in financial risk scenarios.
Explore the application and implementation of cutting-edge research such as large language models, graph neural networks, and multimodal techniques in financial risk scenarios.
Explore the application and implementation of cutting-edge research such as large language models, graph neural networks, and multimodal techniques in financial risk scenarios.
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.
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.
Recognition and rewards for excellence: We grow together with exceptional people — and it’s never too late to join. We’ve enhanced our reward system to recognize high performance, offering more opportunities for outstanding individuals to take on key projects and fully unleash their potential.
Recognition and rewards for excellence: We grow together with exceptional people — and it’s never too late to join. We’ve enhanced our reward system to recognize high performance, offering more opportunities for outstanding individuals to take on key projects and fully unleash their potential.
Recognition and rewards for excellence: We grow together with exceptional people — and it’s never too late to join. We’ve enhanced our reward system to recognize high performance, offering more opportunities for outstanding individuals to take on key projects and fully unleash their potential.
Possess excellent programming skills, data structure, and algorithm skills, proficient in C/C++ or Python programming languages. Priority will be given to those who have won awards in competitions such as ACM/ICPC, NOI/IOI, Top Coder, and Kaggle.
Possess excellent programming skills, data structure, and algorithm skills, proficient in C/C++ or Python programming languages. Priority will be given to those who have won awards in competitions such as ACM/ICPC, NOI/IOI, Top Coder, and Kaggle.
Strong coding skills in at least one of the following programming frameworks, e.g. Python, Java, C/C++, Spark etc.; Familiar with at least one of the following deep learning frameworks, e.g., PyTorch, TensorFlow, Keras etc.
Strong coding skills in at least one of the following programming frameworks, e.g. Python, Java, C/C++, Spark etc.; Familiar with at least one of the following deep learning frameworks, e.g., PyTorch, TensorFlow, Keras etc.
Strong coding skills in at least one of the following programming frameworks, e.g. Python, Java, C/C++, Spark etc.; Familiar with at least one of the following deep learning frameworks, e.g., PyTorch, TensorFlow, Keras etc.
Strong coding skills in at least one of the following programming frameworks, e.g. Python, Java, C/C++, Spark etc.; Familiar with at least one of the following deep learning frameworks, e.g., PyTorch, TensorFlow, Keras etc.
Responsible for the development of deep learning and operations research models and related intelligent systems for the supply chain and logistics of the global E-Commerce business.
Problem Solving for Governance Applications: Address challenges such as long text/sequence modeling, few-shot learning, content moderation, violation detection, and policy recommendation using large models and multimodal approaches.
Problem Solving for Governance Applications: Address challenges such as long text/sequence modeling, few-shot learning, content moderation, violation detection, and policy recommendation using large models and multimodal approaches.
Problem Solving for Governance Applications: Address challenges such as long text/sequence modeling, few-shot learning, content moderation, violation detection, and policy recommendation using large models and multimodal approaches.
Responsible for the development of deep learning and operations research models and related intelligent systems for the supply chain and logistics of the global E-Commerce business.
Problem Solving for Governance Applications: Address challenges such as long text/sequence modeling, few-shot learning, content moderation, violation detection, and policy recommendation using large models and multimodal approaches.