Yi Zhang

RoboDawn is investigated, a human-intuitive interface that exposes robotic control to an agentic VLM through a compact set of discrete translation, rotation, and gripper commands, and an in-context learning (ICL) scheme is introduced that ground the VLM in both interface usage and task-solving strategies.

Routing previously encoded evidence in HR-VQA can yield up to 9.9-point improvements on benchmarks while slashing inference time by over 97%.

High-quality data is all it takes: Bee-8B, trained on the new Honey-Data-15M dataset, leapfrogs existing fully open MLLMs to rival semi-open models.