Paper Citation Record · LEDGER

Torchattacks: A PyTorch Repository for Adversarial Attacks

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 15 inbound Pith citation observations for arXiv:2010.01950.

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

pith.paper-citation-record.v1
2010.01950 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 15 of 15 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:43:05.948566Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-11T02:37:46.246551Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 789d3e10-7335-4959-a107-12f69da58997 · inbound

Towards Generalized Certified Robustness with Multi-Norm Training cites this paper.

Towards Generalized Certified Robustness with Multi-Norm Training Torchattacks: A PyTorch Repository for Adversarial Attacks

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-23T20:03:24.402328Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation bf539ec5-2705-4855-9f5d-23880946a276 · inbound

LLM-Safety Evaluations Lack Robustness cites this paper.

LLM-Safety Evaluations Lack Robustness Torchattacks: A PyTorch Repository for Adversarial Attacks

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-23T01:27:21.222735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 65cd1191-ea96-446b-92b3-91d6b426a845 · inbound

Canonical Latent Representations in Conditional Diffusion Models cites this paper.

Canonical Latent Representations in Conditional Diffusion Models Torchattacks: A PyTorch Repository for Adversarial Attacks

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T04:43:05.948566Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 22e1d19a-6bfc-45dc-8df2-14f2c4ad474d · inbound

FedAPT: Federated Adversarial Prompt Tuning for Vision-Language Models cites this paper.

FedAPT: Federated Adversarial Prompt Tuning for Vision-Language Models Torchattacks: A PyTorch Repository for Adversarial Attacks

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-05T11:18:42.857844Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 618b0d31-3a12-4bb9-b533-c24a5b4da6cc · inbound

Learning Aligned Stability in Neural ODEs Reconciling Accuracy with Robustness cites this paper.

Learning Aligned Stability in Neural ODEs Reconciling Accuracy with Robustness Torchattacks: A PyTorch Repository for Adversarial Attacks

Reference 51

Resolution: verified exact; arxiv_id, observed 2026-05-18T13:12:37.240326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ff189b1d-3cf0-4a57-b4ff-484429028eae · inbound

QShield: Securing Neural Networks Against Adversarial Attacks using Quantum Circuits cites this paper.

QShield: Securing Neural Networks Against Adversarial Attacks using Quantum Circuits Torchattacks: A PyTorch Repository for Adversarial Attacks

Reference 22

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T08:40:57.767629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5d081748-78fb-4e7a-a403-7309b68cad6d · inbound

QShield: Securing Neural Networks Against Adversarial Attacks using Quantum Circuits cites this paper.

QShield: Securing Neural Networks Against Adversarial Attacks using Quantum Circuits Torchattacks: A PyTorch Repository for Adversarial Attacks

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-04T05:31:09.857639Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4ed712e5-8e97-4d0b-b9fd-df92eb416cf5 · inbound

Low Rank Adaptation for Adversarial Perturbation cites this paper.

Low Rank Adaptation for Adversarial Perturbation Torchattacks: A PyTorch Repository for Adversarial Attacks

Reference 94

Resolution: verified exact; arxiv_id, observed 2026-05-12T09:41:25.930229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8641105a-3916-44f4-8aec-44db86dd31b4 · inbound

TAME: Test-Time Adversarial Prompt Tuning via Mixture-of-Experts for Vision-Language Models cites this paper.

TAME: Test-Time Adversarial Prompt Tuning via Mixture-of-Experts for Vision-Language Models Torchattacks: A PyTorch Repository for Adversarial Attacks

Reference 82

Resolution: verified exact; arxiv_id, observed 2026-05-20T14:23:21.480982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation fbbf29ff-a0f5-4913-b97e-3e8e86e021ff · inbound

A combination of noise and bilateral filters achieve supralinear and scalable adversarial robustness in CNNs cites this paper.

A combination of noise and bilateral filters achieve supralinear and scalable adversarial robustness in CNNs Torchattacks: A PyTorch Repository for Adversarial Attacks

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-07-01T22:26:17.823169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation fc9c9381-aefc-4ef6-9219-e776ca20813a · inbound

A Classifier-Agnostic Zero-Shot Adversarial Attack Detection via CLIP cites this paper.

A Classifier-Agnostic Zero-Shot Adversarial Attack Detection via CLIP Torchattacks: A PyTorch Repository for Adversarial Attacks

Reference 14

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T06:44:19.664549Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1f6674bf-643d-407e-8d43-dae61902a4d4 · inbound

A Classifier-Agnostic Zero-Shot Adversarial Attack Detection via CLIP cites this paper.

A Classifier-Agnostic Zero-Shot Adversarial Attack Detection via CLIP Torchattacks: A PyTorch Repository for Adversarial Attacks

Reference 14

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T06:45:29.238686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 98c88676-9718-44c6-92b5-138a9f3f625b · inbound

Two Sides of the Same Coin: Learning the Backdoor to Remove the Backdoor cites this paper.

Two Sides of the Same Coin: Learning the Backdoor to Remove the Backdoor Torchattacks: A PyTorch Repository for Adversarial Attacks

Reference 65

Resolution: metadata mismatch; local_arxiv, observed 2026-07-11T02:37:46.271194Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c97a8057-dcd7-4011-8b11-ba41d0295820 · inbound

Foveation-Guided Dynamic Token Selection for Robust and Efficient Vision Transformers cites this paper.

Foveation-Guided Dynamic Token Selection for Robust and Efficient Vision Transformers Torchattacks: A PyTorch Repository for Adversarial Attacks

Reference 47

Resolution: malformed identifier; no resolver link, observed 2026-07-13T02:43:47.779443Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8c43f685-c089-460c-b8a5-45daad431959 · inbound

Test Case Prioritization for DNNs via Neural Collapse Instability cites this paper.

Test Case Prioritization for DNNs via Neural Collapse Instability Torchattacks: A PyTorch Repository for Adversarial Attacks

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-01T10:59:43.464784Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.