Li Yang

Robots can now reliably act on human gestures by anchoring interaction evidence to specific object instances, achieving over 2x success on implicit intent tasks compared to large VLM baselines.

Human-robot interaction anticipation models exhibit significant directional bias in cue transferability, with pose corrections boosting performance only when transferring from a less to a more visually diverse dataset.