CausalCache: Conditional High-Fidelity Restoration for Long-Horizon GUI Agents

Long-horizon GUI agents can retain complete action histories as compact text, but only a few historical screenshots fit in active context. We formulate this as budgeted fidelity restoration: every event remains summarized, while a fixed budget B determines which events regain their archived screenshots. Recent-B assigns all visual slots to the latest events. CausalCache instead scores the complete history and swaps in an older event only when its predicted utility exceeds that of a recent event. A history-gated key/value adapter modifies only restored history-image tokens and is exactly bypassed when no history image is active, preserving current-screen processing. The adapter and selector are trained with matched-budget interventions on desktop trajectories and evaluated zero-shot on mobile. On OSWorld-Verified, activating historical screenshots improves success by about 13 percentage points over summary-only memory. Under the official 15-step limit, CausalCache and Recent-4 are statistically indistinguishable; in a 30-step diagnostic, CausalCache achieves 46.7% success versus 42.4% (+4.3 points). Zero-shot on 117 MobileWorld tasks, CausalCache improves over Recent-4 from 30.2% to 36.8%. The gain is concentrated on a pre-defined cross-app memory-candidate split (30.6% vs. 19.4%, +11.2 points), while single-app controls show no detectable difference (43.6% vs. 42.4%). These results show that selecting which past events regain pixels is more effective than spending a fixed visual budget entirely on recency.