Synthetic Text Generation using Hypergraph Representations
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Abstract (arXiv)
Generating synthetic variants of a document is often posed as text-to-text transformation. We propose an alternate LLM based method that first decomposes a document into semantic frames and then generates text using this interim sparse format. The frames are modeled using a hypergraph, which allows perturbing the frame contents in a principled manner. Specifically, new hyperedges are mined through topological analysis and complex polyadic relationships including hierarchy and temporal dynamics are accommodated. We show that our solution generates documents that are diverse, coherent and vary in style, sentiment, format, composition and facts.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 22 of its 32 references that are in the map. First posted on arXiv 6 Sep 2023.
Builds on
22 of 32 references.
References · 22
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Citing papers per year: 2026: 1.
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