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Paper Citation Record · LEDGER

DeepFreqMark: End-To-End Learnable Frequency-Domain Watermarking with Spherical Attack Simulation for Latent Diffusion Models

As of 15 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 0 inbound Pith citation observations for arXiv:2608.08999.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2608.08999 v1

Coverage vector

measured 12 of 12 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T04:20:46.404130Z

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

12 of 12 outbound references displayed

  • verified exact1
  • verified fuzzy7
  • unresolved4
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 67c21ee9-52b0-4a39-a0de-761fed9f2a33 · outbound

This paper cites High-resolution image synthesis with latent diffusion models,.

DeepFreqMark: End-To-End Learnable Frequency-Domain Watermarking with Spherical Attack Simulation for Latent Diffusion Models High-resolution image synthesis with latent diffusion models,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:20:46.701530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T04:20:46.337544Z digest=sha256:3267609b51c7d4ee8815c0342ae6a6a5ea1bf6140b35e975d00b3095f8931f47

Observation 77a73387-cfea-4e11-81e5-4a99e9a62b9a · outbound

This paper cites Sdxl: Improving latent diffusion mod- els for high-resolution image synthesis,.

DeepFreqMark: End-To-End Learnable Frequency-Domain Watermarking with Spherical Attack Simulation for Latent Diffusion Models Sdxl: Improving latent diffusion mod- els for high-resolution image synthesis,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:20:46.678056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T04:20:46.343873Z digest=sha256:5d0030a0c78f97f82e30af0aec6531c0c8d5385d376206fa6551be5b9ee97efa

Observation 72a75d52-bfe9-4630-a5f0-e825b7a5cfaa · outbound

This paper cites Latent diffusion models for image watermarking: A review of recent trends and future directions,.

DeepFreqMark: End-To-End Learnable Frequency-Domain Watermarking with Spherical Attack Simulation for Latent Diffusion Models Latent diffusion models for image watermarking: A review of recent trends and future directions,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:20:46.650396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T04:20:46.349380Z digest=sha256:7a2664781c979e6f9ed8bafebcf2b76ba449bfff2d75c64dee91998c802d8e06

Observation 89cf8929-0848-4fd1-a570-914c5babf5a1 · outbound

This paper cites Tree-Ring Watermarks: Fingerprints for Diffusion Images that are Invisible and Robust.

DeepFreqMark: End-To-End Learnable Frequency-Domain Watermarking with Spherical Attack Simulation for Latent Diffusion Models Tree-Ring Watermarks: Fingerprints for Diffusion Images that are Invisible and Robust

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-14T04:20:46.354625Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T04:20:46.354625Z digest=sha256:c781e485a7afd5adde3578414a0f960f4d017a283b1ad94fec77b615466b46a8

Observation 68e58dd2-756c-407f-9900-de0b27c9fab3 · outbound

This paper cites METR: Image Watermarking with Large Number of Unique Messages.

DeepFreqMark: End-To-End Learnable Frequency-Domain Watermarking with Spherical Attack Simulation for Latent Diffusion Models METR: Image Watermarking with Large Number of Unique Messages

Reference 5

Resolution
verified exact
local_arxiv, observed 2026-08-14T04:20:46.498841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T04:20:46.360431Z digest=sha256:9676d46ed35c0a9fbaa7a42500ca4cf574cb059904e839d9bb6ef062f821fdc5

Observation 42fa2126-5536-41c1-b4d3-7e7c3988ad0c · outbound

This paper cites Ringid: Rethinking tree-ring watermarking for enhanced multi- key identification,.

DeepFreqMark: End-To-End Learnable Frequency-Domain Watermarking with Spherical Attack Simulation for Latent Diffusion Models Ringid: Rethinking tree-ring watermarking for enhanced multi- key identification,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:20:46.627926Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T04:20:46.366526Z digest=sha256:dd374164df504ece246a20d3e17b04619ec6c0ef63195c06aa3f14d64318846e

Observation 99588ead-58f3-441d-8fcb-94cf43de3e24 · outbound

This paper cites Semantic watermarking reinvented: Enhancing robustness and generation quality with fourier integrity,.

DeepFreqMark: End-To-End Learnable Frequency-Domain Watermarking with Spherical Attack Simulation for Latent Diffusion Models Semantic watermarking reinvented: Enhancing robustness and generation quality with fourier integrity,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:20:46.607351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T04:20:46.373421Z digest=sha256:d67e99fa83e425459cf5bb2c841ceb505f73ac75e91b9299354a79b18bc35f2d

Observation 7ec01a8f-75b8-4565-abd3-6e9efa8ab0bd · outbound

This paper cites Denoising diffusion implicit models,.

DeepFreqMark: End-To-End Learnable Frequency-Domain Watermarking with Spherical Attack Simulation for Latent Diffusion Models Denoising diffusion implicit models,

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-14T04:20:46.379631Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T04:20:46.379631Z digest=sha256:6dd29d60a2b25a3f870b26225c159d2e592a51de02374bd985ba64c6bcb7694e

Observation 170a9fa9-c92c-4b9e-a9a2-b52e729cedc3 · outbound

This paper cites Learned image compression with discretized gaussian mixture likelihoods and attention modules,.

DeepFreqMark: End-To-End Learnable Frequency-Domain Watermarking with Spherical Attack Simulation for Latent Diffusion Models Learned image compression with discretized gaussian mixture likelihoods and attention modules,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:20:46.561922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T04:20:46.385142Z digest=sha256:def0acf2798072c296cb717847507595fc7013786fc2fa1d6bb972be0bb8e01e

Observation 0ae266d3-118a-46e6-b2e8-0e802bf11913 · outbound

This paper cites Variational image compression with a scale hyperprior.

DeepFreqMark: End-To-End Learnable Frequency-Domain Watermarking with Spherical Attack Simulation for Latent Diffusion Models Variational image compression with a scale hyperprior

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-14T04:20:46.393076Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T04:20:46.393076Z digest=sha256:a90350abedd32d6894d8bdb10cae0c50170e196a0e9544b5a14166817a9570c4

Observation e6d4fdb0-d224-4ed1-bf90-b4fd1abd81e4 · outbound

This paper cites Invisible image watermarks are provably removable using generative ai,.

DeepFreqMark: End-To-End Learnable Frequency-Domain Watermarking with Spherical Attack Simulation for Latent Diffusion Models Invisible image watermarks are provably removable using generative ai,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T04:20:46.541744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T04:20:46.398676Z digest=sha256:30a5f98789917ba8a2e3967ca9c1a385b9e0a9e98f829b9b62686897c5340e91

Observation 39afcd9d-16a3-42bd-bb5f-b0661ccce81a · outbound

This paper cites DiffusionDB: A Large-scale Prompt Gallery Dataset for Text-to-Image Generative Models.

DeepFreqMark: End-To-End Learnable Frequency-Domain Watermarking with Spherical Attack Simulation for Latent Diffusion Models DiffusionDB: A Large-scale Prompt Gallery Dataset for Text-to-Image Generative Models

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-14T04:20:46.404130Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T04:20:46.404130Z digest=sha256:c207c6e2f17670ddc16645c9439f3d5a26eaa971637e5831628f65abbc788b4e

Pith citing papers

No inbound Pith citation observations are available.