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    "headline": "Three-Dimensional Generation Used 70 Percent Fewer Tokens",
    "slug": "three-dimensional-generation-used-70-percent-fewer-tokens",
    "dek": "Sliding-window slice latents preserved cross-sections and long-range topology in one stage.",
    "summary": "Sliding-window slice latents preserved cross-sections and long-range topology in one stage.",
    "body_text": "SILSA represents shapes with overlapping slice latents along three axes rather than fragmented voxel tokens. A sparse decoder and shared volumetric anchor lattice coordinate the slice streams, while persistence-diagram supervision tracks topology between neighbors. Against the strongest reported baseline, SILSA improved PSNR by 8.7 percent, coverage by 5.96 points and Betti error by 9.2 percent while using 70 percent fewer tokens than the next-most compact baseline. These are benchmarked generation results, not guarantees for arbitrary geometry.",
    "why_it_matters": "Sliding-window slice latents preserved cross-sections and long-range topology in one stage.",
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      "These are benchmarked generation results, not guarantees for arbitrary geometry."
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        "qualification": "These are benchmarked generation results, not guarantees for arbitrary geometry."
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    "tags": [
      "3D generation",
      "topology",
      "latent models"
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      "source_id": "source-2026-10-02-008",
      "title": "arXiv preprint 2610.02201",
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    "title": "Three-Dimensional Generation Used 70 Percent Fewer Tokens",
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