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#computer-use

2 articles

01 ·Agents·★ MEMBER·PAPER·10 min read Paper Explained: OSReward — Can You Trust the AI That Grades AI? Remeasuring Rewards for Computer-Use Agents The VLM judges that decide whether an agent driving a PC or a phone succeeded turn out to share a leniency bias that reads failure as success — a paper that exposes it with 1,019 human-verified trajectories and closes the gap with OS-Shepherd, an open reward model 30–60× cheaper, explained from zero background. 02 ·Agents·★ MEMBER·PAPER·8 min read Paper Explained: LongHorizon-Harness — Long-Horizon Agent Tasks Are a State-Management Problem, Not an Execution Problem Without touching the model at all, keeping task state outside execution and running a Manage-Execute-Audit loop dramatically improves long-horizon task performance — a walkthrough of Alibaba DreamX team's harness-design paper, from analogy to pseudocode.