Agibot, which led global humanoid robot shipments in 2025 with 5,168 units, demonstrates production-ready technology through massive robot performance event in Shanghai.

We refer to the proposed solution as SA3D, for Segment Anything in 3D. It is only required to provide a manual segmentation prompt ( e.g., rough points) for the target object in a single view, which is used to generate its 2D mask in this view with SAM.

Thought, the LLM can verbalize that the unknown city is Paris and use this fact to answer downstream questions.

Preferences serve as an alternative but recent work rarely considers preference learning given multiple tasks.

In the continuous pre-training phase, we introduce a hybrid instruction pre-training mechanism to mitigate the internal-injected knowledge inconsistency of LLMs for medical domain adaptation.