Innovative Data Solutions

Combining theoretical analysis with experimental validation for enhanced data generation and model performance.

Innovative Research Solutions

We specialize in counterfactual data augmentation and causal intervention for enhanced data generation and model performance.

A woman is wearing a virtual reality headset and holding controllers in her hands. She is in a laboratory setting with several other people, all wearing lab coats, sitting at a stainless steel table. The background shows more individuals engaged in activities, some interacting with anatomical models.

A dimly lit room features a dark gray sofa against an exposed brick wall. A laptop displaying charts and data is open on the sofa. Light filters through partially open horizontal blinds, casting shadows across the room.

The expected outcomes of this research include: 1) Proposing a causal intervention technique based on counterfactual data augmentation, providing innovative solutions for AI models in complex scenarios; 2) Validating the advantages of this technique in enhancing the causal reasoning ability and generalization performance of models, offering a basis for practical applications; 3) Identifying the limitations of the technique and proposing optimization directions, promoting further development in related fields. These outcomes will help improve the causal reasoning ability of AI models, advance their application in complex scenarios, and provide experimental data and application scenarios for the further optimization of OpenAI models.