עד 90 תווים. תרגום/ניסוח טבעי של הכותרת המקורית: Aim Short to Reach Far: Your Frozen World Model Can Plan Better Than You Think

תקציר מקורי באנגליתarXiv:2609.30036v2 Announce Type: replace Abstract: Planners built on visual world models commonly score each predicted outcome by its distance to the encoded goal image. We show that this target can limit control even with exact dynamics and globally optimal short-horizon search: reaching a goal may require actions that initially move away from it. With frozen LeWM models, intermediate targets substantially improve action synthesis and recorded-action ranking on Cube, PushT, Reacher, and TwoRoom. Learned targets and targets drawn from observed experience both produce these gains. We introduce Anchored Planning, which retrieves a recorded segment whose start and end resemble the current and goal observations, then aims at an observation shortly after its start. The frozen model scores acti