Paper Citation Record · LEDGER

Adaptive Diffusion Denoised Smoothing : Certified Robustness via Randomized Smoothing with Differentially Private Guided Denoising Diffusion

As of 8 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 0 inbound Pith citation observations for arXiv:2507.08163.

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

pith.paper-citation-record.v1
2507.08163 v1

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:36:54.451781Z

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

13 of 13 outbound references displayed

verified exact2
verified fuzzy9
unresolved2
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7d03c6a2-f1d1-422c-a5dc-6ae73da78d90 · outbound

This paper cites (2023) in (a) and with Carlini et al.

Adaptive Diffusion Denoised Smoothing : Certified Robustness via Randomized Smoothing with Differentially Private Guided Denoising Diffusion (2023) in (a) and with Carlini et al

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:54.570952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 814f55ad-740a-43d2-a5c8-c580ea9292a9 · outbound

This paper cites (2023) with 5 votes at every σ.

Adaptive Diffusion Denoised Smoothing : Certified Robustness via Randomized Smoothing with Differentially Private Guided Denoising Diffusion (2023) with 5 votes at every σ

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:54.557707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 62da61f0-e04e-470f-9896-dad2f9bb8c03 · outbound

This paper cites Certified robustness to adversarial examples with differential privacy.

Adaptive Diffusion Denoised Smoothing : Certified Robustness via Randomized Smoothing with Differentially Private Guided Denoising Diffusion Certified robustness to adversarial examples with differential privacy

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:54.638358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 3dd7bb60-d3dd-479f-b3e3-1fa65454199f · outbound

This paper cites Guided Diffusion Model for Adversarial Purification from Random Noise.

Adaptive Diffusion Denoised Smoothing : Certified Robustness via Randomized Smoothing with Differentially Private Guided Denoising Diffusion Guided Diffusion Model for Adversarial Purification from Random Noise

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T18:36:54.426267Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 636870ba-8015-42e3-8d61-2244ee9051fa · outbound

This paper cites Consider a Gaussian mechanism M : x → A(x) + z, where z ∼ N(0, r2 µ2 I) and A is some model.

Adaptive Diffusion Denoised Smoothing : Certified Robustness via Randomized Smoothing with Differentially Private Guided Denoising Diffusion Consider a Gaussian mechanism M : x → A(x) + z, where z ∼ N(0, r2 µ2 I) and A is some model

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:54.624392Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f6ae122a-b201-4c7f-8bbc-2285201d69a7 · outbound

This paper cites This process relies on much stronger assumptions than the RS approach we, Xiao et al.

Adaptive Diffusion Denoised Smoothing : Certified Robustness via Randomized Smoothing with Differentially Private Guided Denoising Diffusion This process relies on much stronger assumptions than the RS approach we, Xiao et al

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:54.611078Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5bb81de9-eab2-4ccb-a468-5a7c96746f65 · outbound

This paper cites To further improve robustness, various methods (Wang et al., 2022; Wu et al., 2022; Bai et al.,.

Adaptive Diffusion Denoised Smoothing : Certified Robustness via Randomized Smoothing with Differentially Private Guided Denoising Diffusion To further improve robustness, various methods (Wang et al., 2022; Wu et al., 2022; Bai et al.,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:54.597166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation add8ce6e-dd0f-480e-8eed-005f478fe6b5 · outbound

This paper cites Guided Diffusion Model for Adversarial Purification.

Adaptive Diffusion Denoised Smoothing : Certified Robustness via Randomized Smoothing with Differentially Private Guided Denoising Diffusion Guided Diffusion Model for Adversarial Purification

Reference 2014

Resolution: unresolved; no resolver link, observed 2026-08-06T18:36:54.422030Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 51b84ca8-d2f8-4dc4-968d-0db2291ff0e5 · outbound

This paper cites Fully Adaptive Composition for Gaussian Differential Privacy.

Adaptive Diffusion Denoised Smoothing : Certified Robustness via Randomized Smoothing with Differentially Private Guided Denoising Diffusion Fully Adaptive Composition for Gaussian Differential Privacy

Reference 2016

Resolution: verified exact; local_arxiv, observed 2026-08-06T18:36:54.522658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 65d6e562-8f14-48c1-9b82-a4c2ca8fc06a · outbound

This paper cites Concurrent composition for interactive differential privacy with adaptive privacy-loss parameters.

Adaptive Diffusion Denoised Smoothing : Certified Robustness via Randomized Smoothing with Differentially Private Guided Denoising Diffusion Concurrent composition for interactive differential privacy with adaptive privacy-loss parameters

Reference 2019

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:54.651752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation fdf61f11-cfb4-4119-9ca4-e27245413201 · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

Adaptive Diffusion Denoised Smoothing : Certified Robustness via Randomized Smoothing with Differentially Private Guided Denoising Diffusion Imagenet: A large-scale hierarchical image database

Reference 2022

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:54.665064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d9f5b578-e175-4c46-9678-835ccb787f3b · outbound

This paper cites Individual Privacy Accounting with Gaussian Differential Privacy.

Adaptive Diffusion Denoised Smoothing : Certified Robustness via Randomized Smoothing with Differentially Private Guided Denoising Diffusion Individual Privacy Accounting with Gaussian Differential Privacy

Reference 2023

Resolution: verified exact; local_arxiv, observed 2026-08-06T18:36:54.543747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d3e272fb-56aa-4027-b57b-da4db42bf461 · outbound

This paper cites Although obtaining empirical accuracy improvement, these methods do not provide provable certification.

Adaptive Diffusion Denoised Smoothing : Certified Robustness via Randomized Smoothing with Differentially Private Guided Denoising Diffusion Although obtaining empirical accuracy improvement, these methods do not provide provable certification

Reference 2024

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:36:54.584363Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Pith citing papers

No inbound Pith citation observations are available.