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CopyShield: A Cross-Level Benchmark of Copyright Defenses in LLMs

arXiv · AI, language, vision and robotics · article · Sep 1, 2026 · UTC

Large language models can reproduce memorized text verbatim, yet copyright defenses are usually evaluated under incompatible protocols. We introduce CopyShield, a controlled benchmark comparing three representative defenses at distinct intervention levels: contrastive decoding (output), Direct Preference Optimization (behavioral), and activation intervention (representation). We evaluate CopyShield on two model families, LLaMA-3.1-8B and Mistral-7B-v0.3, using controlled memorization over five public-domain books and a shared protocol measuring literal leakage, calibrated non-literal leakage,

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Evidence & attribution

First collected: 2026-09-21T06:11:57.537Z. This is not the publication date.