GlanceWAM: Sparse Test-Time Imagination for World-Action Models
GlanceWAM addresses a speed-success trade-off in robot learning models by decoupling future video imagination from real-time control. It achieves this using a dual-timescale approach where slow, asynchronous lookahead frames are generated separately. This allows the system to maintain high control rates while leveraging foresight for superior task success.