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User corrections of AI agents are a goldmine: Echo shows how to automatically transform these noisy interactions into a 10% absolute improvement in code completion acceptance rates.
Decomposing GUI agent trajectories into verifiable milestones and auditing the evidence chain yields a 10% boost in RL training performance, outperforming single-judge reward systems.
