TableNet is a new large-scale table dataset created via LLM multi-agent generation, combined with diversity-based active learning that achieves competitive performance on its test set and superior results on real-world tables using fewer samples than baselines.
InProceedings of the IEEE conference on computer vision and pattern recognition, 9368–9377
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CFMS is a coarse-to-fine framework that uses MLLMs to create a multi-perspective knowledge tuple as a reasoning map for symbolic table operations, yielding competitive accuracy on WikiTQ and TabFact.
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TableNet A Large-Scale Table Dataset with LLM-Powered Autonomous
TableNet is a new large-scale table dataset created via LLM multi-agent generation, combined with diversity-based active learning that achieves competitive performance on its test set and superior results on real-world tables using fewer samples than baselines.
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CFMS: A Coarse-to-Fine Multimodal Synthesis Framework for Enhanced Tabular Reasoning
CFMS is a coarse-to-fine framework that uses MLLMs to create a multi-perspective knowledge tuple as a reasoning map for symbolic table operations, yielding competitive accuracy on WikiTQ and TabFact.
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