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East China Normal University, Shanghai Artificial Intelligence Laboratory
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IA-RAG reveals that modeling knowledge as dynamic time intervals can drastically improve temporal reasoning in language models, outperforming traditional static approaches.
InsightVQA reveals that current models struggle with high-dimensional emotion-cognitive reasoning, exposing critical gaps in visual understanding capabilities.
