arXiv Machine Learning June 25, 2026 By Kasper Green Larsen, Chirag Pabbaraju, Abhishek Shetty

Learning with Monotone Adversarial Corruptions

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arXiv:2601. 02193v2 Announce Type: replace Abstract: We study the extent to which standard machine learning algorithms rely on exchangeability and independence of data by introducing a monotone adversarial corruption model.

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arXiv:2506. 06891v3 Announce Type: replace Abstract: We study the corruption-robustness of in-context reinforcement learning (ICRL), focusing on the Decision-Pretrained Transformer (DPT, Lee et al.

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