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Rendering Graphs for Graph Reasoning in Multimodal Large Language Models
In this paper, we take the first step in incorporating visual information into graph reasoning tasks and propose a new benchmark GITQA, where each sample is a tuple (graph, image, textual description).
Does Misclassifying Non-confounding Covariates as Confounders Affect the Causal Inference within the Potential Outcomes Framework?
Most causal inference models based on the POF (CIMs-POF) are designed for eliminating confounding bias and default to an underlying assumption of Confounding Covariates.
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