Paper Citation Record · LEDGER

Edge-preserving noise for diffusion models

As of 6 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 1 inbound Pith citation observation for arXiv:2410.01540.

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

pith.paper-citation-record.v1
2410.01540 v4

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-23T20:15:13.328348Z

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-12T02:46:18.921562Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-05-12T07:31:24.786340Z

Reference resolution

17 of 17 outbound references displayed

verified exact3
verified fuzzy7
unresolved4
parse uncertain0
malformed identifier2
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 637da55b-ff84-46f3-977a-75822e24d0b8 · outbound

This paper cites URL https://doi.org/10.1214/ aop/1176992362.

Edge-preserving noise for diffusion models URL https://doi.org/10.1214/ aop/1176992362

Reference 1

Resolution: metadata mismatch; arxiv_id, observed 2026-05-23T20:15:47.881693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 6b1edf3b-2566-4745-a542-e6c019ab0903 · outbound

This paper cites Blue noise for diffusion models.

Edge-preserving noise for diffusion models Blue noise for diffusion models

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:15:48.520624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 7eaaf775-9563-4031-b3bb-aa0c89cc31eb · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Edge-preserving noise for diffusion models Adam: A Method for Stochastic Optimization

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-05-23T20:15:48.108697Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 6993f995-95a6-4406-832d-f5fa975675aa · outbound

This paper cites An Improved Evaluation Framework for Generative Adversarial Networks.

Edge-preserving noise for diffusion models An Improved Evaluation Framework for Generative Adversarial Networks

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-05-23T20:15:48.119581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation af99d98e-e724-483c-922e-defae806eb35 · outbound

This paper cites Score-based denoising diffusion with non-isotropic gaussian noise models.

Edge-preserving noise for diffusion models Score-based denoising diffusion with non-isotropic gaussian noise models

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:15:48.560192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 107944db-85f1-4135-bcf2-b4fa3206a4b5 · outbound

This paper cites LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loop.

Edge-preserving noise for diffusion models LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loop

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-05-23T20:15:48.113289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation d1725b28-3008-4b0b-83fa-1d890d2596df · outbound

This paper cites an unresolved cited work.

Edge-preserving noise for diffusion models Unresolved cited work

Reference 7

Resolution: unresolved; raw_fallback, observed 2026-05-23T20:15:48.549081Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 15b81e47-f511-41fd-88c3-c23c4e304ab7 · outbound

This paper cites The motivation for comparing with the latter two works is that they also consider a non-isotropic form of noise.

Edge-preserving noise for diffusion models The motivation for comparing with the latter two works is that they also consider a non-isotropic form of noise

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:15:48.554305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 6436882d-eb68-4e46-bdee-1c34ef6632b3 · outbound

This paper cites an unresolved cited work.

Edge-preserving noise for diffusion models Unresolved cited work

Reference 9

Resolution: unresolved; raw_fallback, observed 2026-05-23T20:15:48.526333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 797e8b6b-c3e3-413b-9de0-c71ad79fb763 · outbound

This paper cites For latent-space diffusion (Rombach et al., 2022), we tested on CelebA (2562) and AFHQ-Cat (5122).

Edge-preserving noise for diffusion models For latent-space diffusion (Rombach et al., 2022), we tested on CelebA (2562) and AFHQ-Cat (5122)

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:15:48.522781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 7ac7081a-389f-4b1e-a85a-8e5ea34d85cf · outbound

This paper cites We trained all datasets on 2x NVIDIA Tesla A40.

Edge-preserving noise for diffusion models We trained all datasets on 2x NVIDIA Tesla A40

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:15:48.519203Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation d6d6b89d-cebf-480b-b2bc-3a4e4385b9a4 · outbound

This paper cites Figure 8, Figure 9, Figure 10, Figure 11 and Figure 12 show more generated samples and comparisons between IHDM, DDPM on all previously introduced datasets.

Edge-preserving noise for diffusion models Figure 8, Figure 9, Figure 10, Figure 11 and Figure 12 show more generated samples and comparisons between IHDM, DDPM on all previously introduced datasets

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:15:48.539644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 91152b58-7b4c-4cdb-8c32-2e9fb2260a52 · outbound

This paper cites an unresolved cited work.

Edge-preserving noise for diffusion models Unresolved cited work

Reference 13

Resolution: malformed identifier; raw_fallback, observed 2026-05-23T20:15:48.515267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 0a497b37-0015-4f7b-8dcb-76564967bf94 · outbound

This paper cites T=500 for Ours, DDPM and Simple Diffusion), and therefore are expected to be faster for inference.

Edge-preserving noise for diffusion models T=500 for Ours, DDPM and Simple Diffusion), and therefore are expected to be faster for inference

Reference 14

Resolution: malformed identifier; raw_fallback, observed 2026-05-23T20:15:48.544313Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation ffdbdcc3-a88e-4f5d-92f2-1c72a3537b2f · outbound

This paper cites an unresolved cited work.

Edge-preserving noise for diffusion models Unresolved cited work

Reference 15

Resolution: unresolved; raw_fallback, observed 2026-05-23T20:15:48.527401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 55d52037-42ed-460e-af03-b39f1eda4b5a · outbound

This paper cites Note how our model is able to generate sharper results that suffer less from artifacts.

Edge-preserving noise for diffusion models Note how our model is able to generate sharper results that suffer less from artifacts

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T20:15:48.530342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 11efe885-9199-436b-9eca-0ac2c29cfcf7 · outbound

This paper cites an unresolved cited work.

Edge-preserving noise for diffusion models Unresolved cited work

Reference 17

Resolution: unresolved; raw_fallback, observed 2026-05-23T20:15:48.534378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Pith citing papers

Observation 7be4d133-b050-4db7-afa7-6ec40932133e · inbound

Score-Based Generative Modeling through Anisotropic Stochastic Partial Differential Equations cites this paper.

Score-Based Generative Modeling through Anisotropic Stochastic Partial Differential Equations Edge-preserving noise for diffusion models

Reference 29

Resolution: metadata mismatch; local_arxiv, observed 2026-05-12T07:31:24.791670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.