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Northeastern University
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A hierarchical agent that separates visual and textual contexts drastically improves multi-step reasoning on complex charts, outperforming monolithic MLLMs.
LLMs struggle with causal reasoning when noise is introduced, but explicitly modeling causal graphs can dramatically improve performance and generalization.
Video LLMs don't just get details wrong, they fundamentally distort motion and fabricate entire events, demanding a new approach to evaluation and mitigation.
