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During poisoning, a trigger is injected into the forced-aligned time span of a chosen source word in the audio and replace only that word in the transcript, enabling precise semantic flips and composable sentence manipulation while avoiding many-to-one label artifacts.
Maxsoft is introduced—a novel MIL pooling function that enables flexible control over this trade-off, allowing adaptation to specific tasks and datasets, and PerPatch augmentation is proposed—a simple yet effective technique that enhances model robustness.
Large vision--language models (LVLMs) demonstrate strong multimodal reasoning capabilities but remain prone to hallucination, where model predictions are not grounded in visual evidence, so a fully black-box framework that models hallucination as a structured uncertainty pattern is proposed.
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