STC reduces tabular chunk counts by up to 56% versus baselines and raises hybrid MRR to 0.5945 and BM25 Recall@1 to 0.754 by preserving row structure during chunking.
Turl: Table understanding through representation learning
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
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TabEmb decouples LLM-based semantic column embeddings from graph-based structural modeling to produce joint representations that improve table annotation tasks.
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Structure-Aware Chunking for Tabular Data in Retrieval-Augmented Generation
STC reduces tabular chunk counts by up to 56% versus baselines and raises hybrid MRR to 0.5945 and BM25 Recall@1 to 0.754 by preserving row structure during chunking.
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TabEmb: Joint Semantic-Structure Embedding for Table Annotation
TabEmb decouples LLM-based semantic column embeddings from graph-based structural modeling to produce joint representations that improve table annotation tasks.