EvoCUA-8B

LearnWeak: Automated Domain Specialization for Small Computer-Use Agents via Weakness-Targeted Synthesis

LearnWeak is an annotation-free framework for specializing small computer-use agents (CUAs) in specific software domains without deploying large expert models. It uses a stronger reference agent to identify weaknesses in a smaller student agent, synthesizes targeted tasks, and applies an error-aware training objective that disentangles planning from execution errors. On OSWorld, LearnWeak achieves gains of ~11 percentage points over 7B-8B baseline CUAs across eight domains. The work demonstrates that student-aware data synthesis substantially outperforms naive large-scale data generation for domain specialization.