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A Few Teacher Steps Go a Long Way: Cost-Efficient On-Policy Data Augmentation for Agent Post-Training

Bounded unfiltered teacher continuations at learner-induced contexts improve over pure behavioral cloning at matched budgets and suggest that a few teacher steps, placed at learner-induced contexts, can be a more cost-efficient supervision allocation than longer or more heavily curated teacher completions.

Junze Ye, Jiayi Cheng, Miao Lu et al. · 2 citations

Robust Assortment Optimization from Observational Data

This work uncover and identify the notion of ``robust item-wise coverage''as the minimal data requirement to enable sample-efficient robust assortment learning and bridges the gap between robustness and statistical efficiency in assortment learning.

Miao Lu, Yuxuan Han, Han Zhong et al. · 0 citations

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