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Seoul National University
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Content correctness masks widespread structural failure: 38% of otherwise accurate LLM outputs silently break CommonMark delimiter boundaries, crippling downstream parsers and execution pipelines.
SRAP achieves a remarkable trade-off, enhancing image fidelity while maintaining robust identity disruption against face-swapping attacks.
