Model card: FARPO expansion as in the paper

README.md

@@ -11,7 +11,7 @@ Anonymous release for the ICLR 2027 submission *MemGUI-RL: Reinforcement Learnin
 Context Management in Long-Horizon Mobile GUI Agents*. Project page: https://memgui-rl-anonymous.github.io/
 
 MemGUI-8B-RL is MemGUI-8B-SFT (Qwen3-VL-8B-Instruct supervised on MemGUI-3K) post-trained for 100
-optimizer steps with **FARPO** (Folding-Aware Reward-decoupled Policy Optimization, span-to-step ratio
+optimizer steps with **FARPO** (Folding-Aware Reward-Decoupled Policy Optimization, span-to-step ratio
 rho = 9). The policy speaks the ConAct (Context-as-Action) interface of MemGUI-Agent: every response
 contains a folding directive for its own history, an optional memory operation and the next GUI action.