Xiaosong Jia

“GuidedVLA demonstrates that VLA models fail not because they lack capability, but because their action decoders latch onto irrelevant visual noise — and fixing this with explicit, targeted supervision yields consistent 10-20% performance gains across both simulation and real hardware, without retraining the base model.”

“the depth head alone improves performance on the 'Click Bell' precision task (requiring Z-axis control) from 35% to 63%; the skill head prevents stage-collapse on long-horizon tasks; the object head raises scores on cluttered-scene tasks by +8.4% over π₀ on the LIBERO-Plus Object suite.”

“Xiaosong Jia, Fudan University (TEAI / Shanghai Key Lab of Multimodal Embodied AI). Project lead and primary technical architect of GuidedVLA. Also co-author of Interleave-VLA.”