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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2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
UNVERDICTED 2representative citing papers
STR rewrites table cells as <item path, feature path, value> triplets and uses TripletQL to match or exceed HTML baselines on four benchmarks while cutting tokens.
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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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Semantic Triplet Restoration: A Novel Protocol for Hierarchical Table Understanding in Large Language Models
STR rewrites table cells as <item path, feature path, value> triplets and uses TripletQL to match or exceed HTML baselines on four benchmarks while cutting tokens.