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Candidate answer-side concepts infiltrate 7.40% of LLM-generated queries, challenging the integrity of information retrieval evaluations.
VLMs often rely on misleading visual cues instead of true chronological understanding, revealing critical flaws in their reasoning capabilities.
Multimodal graph unlearning doesn't have to destroy utility: carefully protecting high-dimensional input projections during the unlearning process preserves performance while still enabling effective forgetting.
