About Us

Model Fusion & Model Merging

Model Merging: Combining homogeneous models with the same architecture directly in parameter space (e.g., weight averaging, task vectors) to produce a single checkpoint with baseline-like inference cost.

Model Fusion: Combining heterogeneous or homogeneous models in prediction/knowledge space (ensembles, logit averaging, distillation, FL aggregation). Ensembles raise inference cost, while distillation returns a compact model.

Reasoning-Enhanced Low-Resource Training

We develop methods to create highly capable AI systems that require minimal computational resources, making advanced AI accessible to organizations of all sizes through techniques like FP8 precision training, edge AI deployment, and privacy-preserving solutions.

Advanced Vision-Native Agent for GUI Interaction

InfiGUIAgent: A GUI agent that embeds native hierarchical and expectation-reflection reasoning through a unique two-stage supervised pipeline, enabling robust, multi-step GUI task automation.

InfiGUI-R1: A GUI agent developed via the Actor2Reasoner framework, which evolves a reactive model into a deliberative reasoner capable of sophisticated planning and error recovery through spatial reasoning distillation and reinforcement learning.