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VisionQ is introduced, the first benchmark built from peer-reviewed CV comparison figures that grounds every judgment in a named visual criterion: each question states the criterion, and a judge is credited only when it selects the output the authors identify as best on that criterion.
VIVID is presented, the first systematic benchmark for evaluating culturally grounded figurative language understanding in Vietnamese, and an evaluation framework combining generative and discriminative tasks, proposing an LLM-as-a-Judge approach with aspect-based prompting validated against human judgment.
This survey presents a unified and pipeline-aware overview of RAG robustness, formalize threat models over the corpus, retriever, and generator, and organize attacks into three main objectives: accuracy, privacy, and fairness.
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