Papers by David Rabinowitz

    1 papers
    Domain Generalizable AI Guardrails with Augmented Policy Training (2026.acl-long)

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    Challenge: Current guardrails overfit the training policies, preventing adaptation to new domains and policies.
    Approach: They propose a training recipe that uses a suite of policy perturbation strategies to reduce overfitting and increase generalization to guardrails.
    Outcome: The proposed training recipe reduces overfitting and increases generalization on unseen policies and achieves comparable or better performance than existing 8B guardrails on unsen policies.

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