Design of Reward Models: In the RL process, designing an effective reward model is crucial. It must accurately reflect the effectiveness of the reasoning process and guide the model to iteratively improve its reasoning ability. This involves not only setting appropriate evaluation criteria across different tasks, but also ensuring the reward model to adapt dynamically during training to match the evolving model performance.
Design of Reward Models: In the RL process, designing an effective reward model is crucial. It must accurately reflect the effectiveness of the reasoning process and guide the model to iteratively improve its reasoning ability. This involves not only setting appropriate evaluation criteria across different tasks, but also ensuring the reward model to adapt dynamically during training to match the evolving model performance.
Co-create with the team: Creativity is at the core of our business. Whether it's building the product or shaping the team, we strive to spark imagination and deliver impact — for ourselves, the platform, the communities we serve, and society as a whole.
Co-create with the team: Creativity is at the core of our business. Whether it's building the product or shaping the team, we strive to spark imagination and deliver impact — for ourselves, the platform, the communities we serve, and society as a whole.
Co-create with the team: Creativity is at the core of our business. Whether it's building the product or shaping the team, we strive to spark imagination and deliver impact — for ourselves, the platform, the communities we serve, and society as a whole.
Co-create with the team: Creativity is at the core of our business. Whether it's building the product or shaping the team, we strive to spark imagination and deliver impact — for ourselves, the platform, the communities we serve, and society as a whole.
Data enhancement algorithm optimization: Design a data-centric algorithm framework for data reasoning tasks, optimize the Reasoning Data synthesis pipeline, and improve the logical consistency, domain adaptability, and diversity of training data.
Data enhancement algorithm optimization: Design a data-centric algorithm framework for data reasoning tasks, optimize the Reasoning Data synthesis pipeline, and improve the logical consistency, domain adaptability, and diversity of training data.
Data enhancement algorithm optimization: Design a data-centric algorithm framework for data reasoning tasks, optimize the Reasoning Data synthesis pipeline, and improve the logical consistency, domain adaptability, and diversity of training data.
Data enhancement algorithm optimization: Design a data-centric algorithm framework for data reasoning tasks, optimize the Reasoning Data synthesis pipeline, and improve the logical consistency, domain adaptability, and diversity of training data.
Data enhancement algorithm optimization: Design a data-centric algorithm framework for data reasoning tasks, optimize the Reasoning Data synthesis pipeline, and improve the logical consistency, domain adaptability, and diversity of training data.
Enhance the multimodal perception encoder: The current encoder uses a fixed frame rate. We need to explore more efficient adaptive frame rates while considering the integration of modalities such as audio and user behavior.
Enhance the multimodal perception encoder: The current encoder uses a fixed frame rate. We need to explore more efficient adaptive frame rates while considering the integration of modalities such as audio and user behavior.
Responsible for building and continuously optimizing algorithm solutions in product profiling construction & product information quality improvement etc. to accelerate supply operational efficiencies in global e-commerce markets;
Responsible for building and continuously optimizing algorithm solutions in product profiling construction & product information quality improvement etc. to accelerate supply operational efficiencies in global e-commerce markets;
Responsible for building and continuously optimizing algorithm solutions in product profiling construction & product information quality improvement etc. to accelerate supply operational efficiencies in global e-commerce markets;
Responsible for building and continuously optimizing algorithm solutions in product profiling construction & product information quality improvement etc. to accelerate supply operational efficiencies in global e-commerce markets;
Build global logistic and warehousing network, improve operations efficiency and reduce operational cost with data analysis, machine learning and operation research methods.
Large language Model Algorithm Development: Build domain-specific large language models (LLM/MLLM) for e-commerce, integrating domain knowledge to rapidly apply models to business scenarios.
Large language Model Algorithm Development: Build domain-specific large language models (LLM/MLLM) for e-commerce, integrating domain knowledge to rapidly apply models to business scenarios.
Large language Model Algorithm Development: Build domain-specific large language models (LLM/MLLM) for e-commerce, integrating domain knowledge to rapidly apply models to business scenarios.
Build global logistic and warehousing network, improve operations efficiency and reduce operational cost with data analysis, machine learning and operation research methods.