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Budget-aware evaluation for Active RAG evaluation is studied by recasting active retrieval as utility estimation, where retrieval is valuable only through its marginal correctness change over a no-retrieval answer.
This work constructs a benchmark that captures unintended degradation on benign inputs sharing generic patterns with the forget set, and proposes Selective Protection with Anchored Regularization, which protects generic patterns via anchored activation filtering while reinforcing them through entity-abstracted enhancem...
A minimal benchmark design and candidate reporting metrics for user-conditioned adaptation are proposed and a concrete design requirement for future personal-agent evaluation, with metrics used as reporting tools for that requirement.
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