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Real-generation experiments that account for the pilot synchronization barrier show that HBN-async mitigates its overhead, helping translate statistical efficiency into practical evaluation benefits, and outperforming hindsight-tuned empirical and independent Bayesian baselines.
TrajVal, a lightweight probe-based estimator that approximates per-task learnability from a short probe run and two endpoint evaluations, is proposed and it is found that learnability is reproducible across independently sampled training contexts and predictive of downstream utility.
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