Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-15T17:48:22.613699Z
Paper Citation Record · LEDGER
As of 16 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2507.21195.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-15T17:48:22.613699Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
45 of 45 outbound references displayed
External citation measurements
No source-named external measurement is stored.
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MaXsive: High-Capacity and Robust Training-Free Generative Image Watermarking in Diffusion Models Unresolved cited work
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MaXsive: High-Capacity and Robust Training-Free Generative Image Watermarking in Diffusion Models Hidden in the Noise: Two-Stage Robust Watermarking for Images
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MaXsive: High-Capacity and Robust Training-Free Generative Image Watermarking in Diffusion Models Unresolved cited work
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MaXsive: High-Capacity and Robust Training-Free Generative Image Watermarking in Diffusion Models Bas, J.-M
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MaXsive: High-Capacity and Robust Training-Free Generative Image Watermarking in Diffusion Models Provisions on the Administration of Deep Synthesis Internet Information Services
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MaXsive: High-Capacity and Robust Training-Free Generative Image Watermarking in Diffusion Models Unresolved cited work
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MaXsive: High-Capacity and Robust Training-Free Generative Image Watermarking in Diffusion Models Unresolved cited work
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MaXsive: High-Capacity and Robust Training-Free Generative Image Watermarking in Diffusion Models Brankov, N.P
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MaXsive: High-Capacity and Robust Training-Free Generative Image Watermarking in Diffusion Models Brankov, Nikolas P
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MaXsive: High-Capacity and Robust Training-Free Generative Image Watermarking in Diffusion Models Unresolved cited work
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MaXsive: High-Capacity and Robust Training-Free Generative Image Watermarking in Diffusion Models Unresolved cited work
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MaXsive: High-Capacity and Robust Training-Free Generative Image Watermarking in Diffusion Models Unresolved cited work
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MaXsive: High-Capacity and Robust Training-Free Generative Image Watermarking in Diffusion Models Unresolved cited work
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MaXsive: High-Capacity and Robust Training-Free Generative Image Watermarking in Diffusion Models Unresolved cited work
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MaXsive: High-Capacity and Robust Training-Free Generative Image Watermarking in Diffusion Models Shi, and Yan Lin
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MaXsive: High-Capacity and Robust Training-Free Generative Image Watermarking in Diffusion Models Unresolved cited work
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MaXsive: High-Capacity and Robust Training-Free Generative Image Watermarking in Diffusion Models Bhattacharjee, and Touradj Ebrahimi
Reference 17
Source-reported events for the cited work
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MaXsive: High-Capacity and Robust Training-Free Generative Image Watermarking in Diffusion Models Bloom, Ingemar J
Reference 18
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MaXsive: High-Capacity and Robust Training-Free Generative Image Watermarking in Diffusion Models Unresolved cited work
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MaXsive: High-Capacity and Robust Training-Free Generative Image Watermarking in Diffusion Models Unresolved cited work
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MaXsive: High-Capacity and Robust Training-Free Generative Image Watermarking in Diffusion Models Unresolved cited work
Reference 21
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MaXsive: High-Capacity and Robust Training-Free Generative Image Watermarking in Diffusion Models Unresolved cited work
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MaXsive: High-Capacity and Robust Training-Free Generative Image Watermarking in Diffusion Models Unresolved cited work
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MaXsive: High-Capacity and Robust Training-Free Generative Image Watermarking in Diffusion Models Unresolved cited work
Reference 24
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MaXsive: High-Capacity and Robust Training-Free Generative Image Watermarking in Diffusion Models Unresolved cited work
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MaXsive: High-Capacity and Robust Training-Free Generative Image Watermarking in Diffusion Models Ò Ruanaidh and Thierry Pun
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MaXsive: High-Capacity and Robust Training-Free Generative Image Watermarking in Diffusion Models Unresolved cited work
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MaXsive: High-Capacity and Robust Training-Free Generative Image Watermarking in Diffusion Models Petitcolas
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MaXsive: High-Capacity and Robust Training-Free Generative Image Watermarking in Diffusion Models Petitcolas, Ross J
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MaXsive: High-Capacity and Robust Training-Free Generative Image Watermarking in Diffusion Models Synthetic Shifts to Initial Seed Vector Exposes the Brittle Nature of Latent-Based Diffusion Models
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MaXsive: High-Capacity and Robust Training-Free Generative Image Watermarking in Diffusion Models Unresolved cited work
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MaXsive: High-Capacity and Robust Training-Free Generative Image Watermarking in Diffusion Models Unresolved cited work
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MaXsive: High-Capacity and Robust Training-Free Generative Image Watermarking in Diffusion Models Unresolved cited work
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MaXsive: High-Capacity and Robust Training-Free Generative Image Watermarking in Diffusion Models Unresolved cited work
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MaXsive: High-Capacity and Robust Training-Free Generative Image Watermarking in Diffusion Models Unresolved cited work
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MaXsive: High-Capacity and Robust Training-Free Generative Image Watermarking in Diffusion Models Unresolved cited work
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MaXsive: High-Capacity and Robust Training-Free Generative Image Watermarking in Diffusion Models InvisMark: Invisible and Robust Watermarking for AI-generated Image Provenance
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MaXsive: High-Capacity and Robust Training-Free Generative Image Watermarking in Diffusion Models Unresolved cited work
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MaXsive: High-Capacity and Robust Training-Free Generative Image Watermarking in Diffusion Models Zheng, J
Reference 42
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MaXsive: High-Capacity and Robust Training-Free Generative Image Watermarking in Diffusion Models Unresolved cited work
Reference 43
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MaXsive: High-Capacity and Robust Training-Free Generative Image Watermarking in Diffusion Models Similarly, the top boundary of 𝑆 is at 𝑦 = 𝑛; thus, for 𝑆 to be contained in𝑅, we must have 𝑛≤ 𝑁 2 sin𝜃−𝑛 cos𝜃 2 sin𝜃 +𝑛 2, which implies that 𝑛≤ 𝑁 sin𝜃+ cos𝜃
Reference 46
Source-reported events for the cited work
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MaXsive: High-Capacity and Robust Training-Free Generative Image Watermarking in Diffusion Models In 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Reference 2024
Source-reported events for the cited work
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No inbound Pith citation observations are available.