Guanjun Jiang

Treating all latent tokens identically bottlenecks multimodal test-time compute—disentangling hidden-state updates into visual-grounding and high-entropy reasoning channels beats standard output-space search under matched sample budgets.

Chasing large token-level teacher-student gaps in agent distillation is largely misguided: local divergence fails to predict task completion, whereas unpenalized minor deviations often trigger catastrophic multi-turn failure.

Iapetus achieves a remarkable 91.6% task completion rate while slashing mean latency and battery draw by over 50% in satellite-based ViT inference.