Pith. sign in

Paper Citation Record · LEDGER

Adversarial Robustness Toolbox v1.0.0

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 27 inbound Pith citation observations for arXiv:1807.01069.

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

pith.paper-citation-record.v1
1807.01069 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 27 of 27 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T23:12:49.381724Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T07:09:38.818399Z

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 f5ea9337-a985-4565-8914-c733db3353a7 · inbound

Measuring the Transferability of Adversarial Examples cites this paper.

Measuring the Transferability of Adversarial Examples Adversarial Robustness Toolbox v1.0.0

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-24T21:29:57.928299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-24T21:26:53.670675Z digest=sha256:0e532c66dd35c3404e9949749b3f1676af5f69b20e0b294b9556ef3373bdafe2

Observation 55f34aeb-6f49-428c-8f46-30cd6f758205 · inbound

Survival of the Cheapest: Cost-Aware Hardware Adaptation for Adversarial Robustness cites this paper.

Survival of the Cheapest: Cost-Aware Hardware Adaptation for Adversarial Robustness Adversarial Robustness Toolbox v1.0.0

Reference 26

Resolution
metadata mismatch
arxiv_id, observed 2026-05-23T21:15:49.317389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-23T21:14:38.949892Z digest=sha256:dba9279c83582454b45a8ccb7824538c8b05d7545aa8fedf305f267780385e3f

Observation 058bd55b-e367-454d-ae4c-551a16dc40e6 · inbound

Safeguarding connected autonomous vehicle communication: Protocols, intra- and inter-vehicular attacks and defenses cites this paper.

Safeguarding connected autonomous vehicle communication: Protocols, intra- and inter-vehicular attacks and defenses Adversarial Robustness Toolbox v1.0.0

Reference 173

Resolution
unresolved
no resolver link, observed 2026-08-08T23:12:49.381724Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T23:12:49.381724Z digest=sha256:25826b9e5da0378982f9af94c91ee3c055d3bc2c0f183434052a7779ffdf6588

Observation 61eaeae6-d6a3-4d91-9027-1d7983e43aee · inbound

DURA-CPS: A Multi-Role Orchestrator for Dependability Assurance in LLM-Enabled Cyber-Physical Systems cites this paper.

DURA-CPS: A Multi-Role Orchestrator for Dependability Assurance in LLM-Enabled Cyber-Physical Systems Adversarial Robustness Toolbox v1.0.0

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-07T10:45:41.090835Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:45:41.090835Z digest=sha256:8476104690822fcb0fd9411c277b9069133e496fb3921b03830302add42598aa

Observation fe047785-449a-4bba-8fc8-9cf6eb721425 · inbound

SDN-Based False Data Detection With Its Mitigation and Machine Learning Robustness for In-Vehicle Networks cites this paper.

SDN-Based False Data Detection With Its Mitigation and Machine Learning Robustness for In-Vehicle Networks Adversarial Robustness Toolbox v1.0.0

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-07T05:58:20.766497Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:58:20.766497Z digest=sha256:44ebdada31871f6c9cda2d29ce3bb2990adc5981a0dac33a26f8a3e240c2203e

Observation 404855ee-5ebc-445b-8c2b-ca9cd27dec19 · inbound

An Attack Method for Medical Insurance Claim Fraud Detection based on Generative Adversarial Network cites this paper.

An Attack Method for Medical Insurance Claim Fraud Detection based on Generative Adversarial Network Adversarial Robustness Toolbox v1.0.0

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-06T23:27:52.142469Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:27:52.142469Z digest=sha256:db8880e90961be107d12098f0a6430a488a7087ff18ed4cdeb480aa5a56bcd6f

Observation c42ebb42-a6d2-4e01-8f55-c2fd298bbd5c · inbound

Securing AI Systems: A Guide to Known Attacks and Impacts cites this paper.

Securing AI Systems: A Guide to Known Attacks and Impacts Adversarial Robustness Toolbox v1.0.0

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-06T21:50:27.050580Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:50:27.050580Z digest=sha256:6bd7295e90a522b7d1bc13c166fb18aee399a4bfd6b205fabaf8d4637d5e9fce

Observation fcb312f9-f28e-4d24-b575-aa13b0952d13 · inbound

Leveraging Trustworthy AI for Automotive Security in Multi-Domain Operations: Towards a Responsive Human-AI Multi-Domain Task Force for Cyber Social Security cites this paper.

Leveraging Trustworthy AI for Automotive Security in Multi-Domain Operations: Towards a Responsive Human-AI Multi-Domain Task Force for Cyber Social Security Adversarial Robustness Toolbox v1.0.0

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-06T14:51:29.025105Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:51:29.025105Z digest=sha256:d361ea9fb97b18ee9910fb44ffd44e7a5959eab8bd081ec43b5b89eb83ffb32a

Observation 3b615e48-459f-49c0-9ee0-f71ad2e4877c · inbound

Privacy-Utility Trade-off in Data Publication: A Bilevel Optimization Framework with Curvature-Guided Perturbation cites this paper.

Privacy-Utility Trade-off in Data Publication: A Bilevel Optimization Framework with Curvature-Guided Perturbation Adversarial Robustness Toolbox v1.0.0

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-05T11:59:40.429887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T11:59:40.429887Z digest=sha256:65a1a105a0f2a4a2744588ccb5d3ae639c59d67b39dbbfda30cb183b6612bb58

Observation 4e61db9c-cf58-4998-acdb-f9bcb98c17b3 · inbound

UNDREAM: Bridging Differentiable Rendering and Photorealistic Simulation for End-to-end Adversarial Attacks cites this paper.

UNDREAM: Bridging Differentiable Rendering and Photorealistic Simulation for End-to-end Adversarial Attacks Adversarial Robustness Toolbox v1.0.0

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-04T09:10:41.351794Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T09:10:41.351794Z digest=sha256:3542334dc02c4573d0805e1177e60478d2ad71ba8f0ea0706bf23b792d5121a7

Observation 2b92b428-0b30-48d3-ade2-677e5317f9ec · inbound

Lipschitz-Based Robustness Certification Under Floating-Point Execution cites this paper.

Lipschitz-Based Robustness Certification Under Floating-Point Execution Adversarial Robustness Toolbox v1.0.0

Reference 37

Resolution
unresolved
no resolver link, observed 2026-07-15T14:07:56.936206Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-15T14:07:56.936206Z digest=sha256:ddd6c4c2642dba464de549c4b27ed07b744ed32feff26cfcd3382faa91822575

Observation 1113e6c8-2b04-4507-a19c-f8b4a0e8f3d0 · inbound

Lipschitz-Based Robustness Certification Under Floating-Point Execution cites this paper.

Lipschitz-Based Robustness Certification Under Floating-Point Execution Adversarial Robustness Toolbox v1.0.0

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-02T18:47:59.430867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T18:47:59.430867Z digest=sha256:79dd3ba68baef5e597b78962a58d947806bab1c291960836b7ad8f194acfe939

Observation 1127e324-e9b0-477d-bdab-acfa2c8b4a81 · inbound

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

QShield: Securing Neural Networks Against Adversarial Attacks using Quantum Circuits Adversarial Robustness Toolbox v1.0.0

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-05-11T08:40:57.754023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T16:35:01.080061Z digest=sha256:46d4efc5d2547240476a9ab150f5baa632ba14e7412b0e7d1af4414bbd028765

Observation 4b0fd0ce-8dfc-4cfe-84fe-5092e27167b8 · inbound

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

QShield: Securing Neural Networks Against Adversarial Attacks using Quantum Circuits Adversarial Robustness Toolbox v1.0.0

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-04T05:31:09.910840Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T05:31:09.910840Z digest=sha256:f0584c178748fe61428554f6b234d6176ed937e5751bf481652b626d9d1c3e57

Observation 1d8f6f48-c4a2-4b0b-a2df-948dbe0fe04a · inbound

Evaluating Differential Privacy Against Membership Inference in Federated Learning: Insights from the NIST Genomics Red Team Challenge cites this paper.

Evaluating Differential Privacy Against Membership Inference in Federated Learning: Insights from the NIST Genomics Red Team Challenge Adversarial Robustness Toolbox v1.0.0

Reference 10

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T09:00:58.155268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T16:22:32.081448Z digest=sha256:e96146bca40d4724ba7f4be64e9128c86a9fbcea5341fd11f71fd8a8ba7ea3e8

Observation 5682dedc-ffa7-4dfc-bd89-0881b3f6fcbe · inbound

Auto-ART: Structured Literature Synthesis and Automated Adversarial Robustness Testing cites this paper.

Auto-ART: Structured Literature Synthesis and Automated Adversarial Robustness Testing Adversarial Robustness Toolbox v1.0.0

Reference 20

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T00:39:48.191438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T00:39:43.196010Z digest=sha256:0bc2cfb7db47232d3b99f56f307736ef05e10119e745143c1f1cf01e95bea0f0

Observation 6b9220d7-af71-4a84-b884-ba5f45cf1f51 · inbound

AVISE: Framework for Evaluating the Security of AI Systems cites this paper.

AVISE: Framework for Evaluating the Security of AI Systems Adversarial Robustness Toolbox v1.0.0

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-05-10T00:24:47.405852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T00:07:04.164983Z digest=sha256:98b8592f0d729adb7bda9a48112b8171bcf9d82d11148f277c5b0c8484151b4e

Observation 1dd57bf5-f8c5-4a4a-95cd-afcdcf12b31e · inbound

Multi-Dimensional Model Integrity and Responsibility Assessment Index and Scoring Framework cites this paper.

Multi-Dimensional Model Integrity and Responsibility Assessment Index and Scoring Framework Adversarial Robustness Toolbox v1.0.0

Reference 20

Resolution
metadata mismatch
arxiv_id, observed 2026-05-15T01:59:38.872766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-15T01:58:50.023224Z digest=sha256:bfcf612b4dcbe6a3ac238fb35614e4b09639e0476e2d8e3281c53bdd30928541

Observation dd397cb2-6659-4d83-a7df-4958dc74e032 · inbound

SAFE Quantum Machine Learning with Variational Quantum Classifiers cites this paper.

SAFE Quantum Machine Learning with Variational Quantum Classifiers Adversarial Robustness Toolbox v1.0.0

Reference 64

Resolution
metadata mismatch
arxiv_id, observed 2026-05-20T20:49:00.594638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-20T20:48:51.326460Z digest=sha256:cf97414bd6ff1a1acc8a8606cf16850f82550f2889f23bf67040c4058f2ecc9b

Observation 1f65d54e-cd75-4574-acad-d39c82be447e · inbound

Adversarial Fragility and Language Vulnerability in Clinical AI: A Systematic Audit of Diagnostic Collapse Under Imperceptible Perturbations and Cross-Lingual Drift in Low-Resource Healthcare Settings cites this paper.

Adversarial Fragility and Language Vulnerability in Clinical AI: A Systematic Audit of Diagnostic Collapse Under Imperceptible Perturbations and Cross-Lingual Drift in Low-Resource Healthcare Settings Adversarial Robustness Toolbox v1.0.0

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-19T19:22:44.783451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-19T19:19:27.683820Z digest=sha256:1a2b202a8f29196534001d6e01441efa459fc67edd218dbdd8f7fce2c5cd9227

Observation d2bbb91b-5f27-4d6d-bb7a-945ac7309a8f · inbound

STRIDE-AI: A Threat Modeling Framework for Generative AI Security Assessment cites this paper.

STRIDE-AI: A Threat Modeling Framework for Generative AI Security Assessment Adversarial Robustness Toolbox v1.0.0

Reference 13

Resolution
metadata mismatch
arxiv_id, observed 2026-05-20T14:18:21.330037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-20T14:15:04.206931Z digest=sha256:65a6cb8adf57c2e140db7d72d08f0bf980749f8f5b0c03846cd1733ed0142a79

Observation 0a740d65-88fa-46a8-b89b-bd38f385f6b6 · inbound

FML-bench: A Controlled Study of AI Research Agent Strategies from the Perspective of Search Dynamics cites this paper.

FML-bench: A Controlled Study of AI Research Agent Strategies from the Perspective of Search Dynamics Adversarial Robustness Toolbox v1.0.0

Reference 37

Resolution
metadata mismatch
arxiv_id, observed 2026-05-20T14:28:21.477850Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-20T14:25:15.565386Z digest=sha256:d93a85d0a7c1781a19c7cbfb7788827700998c1a033e6b497daf70922ccf9528

Observation b08a790f-e61d-45ff-8c74-1378d6851c8c · inbound

FML-bench: A Controlled Study of AI Research Agent Strategies from the Perspective of Search Dynamics cites this paper.

FML-bench: A Controlled Study of AI Research Agent Strategies from the Perspective of Search Dynamics Adversarial Robustness Toolbox v1.0.0

Reference 37

Resolution
metadata mismatch
arxiv_id, observed 2026-06-30T19:05:00.936374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-30T19:00:30.961402Z digest=sha256:ac0502a2f854bb9c7ba7a78b20a312ce96260024ad33badb4b163e159cf8ec77

Observation c5beb819-6b94-4256-bd32-65ba43a2c05b · inbound

A No-Defense Defense Against Gradient-Based Adversarial Attacks on ML-NIDS: Is Less More? cites this paper.

A No-Defense Defense Against Gradient-Based Adversarial Attacks on ML-NIDS: Is Less More? Adversarial Robustness Toolbox v1.0.0

Reference 20

Resolution
metadata mismatch
arxiv_id, observed 2026-05-20T13:18:18.269497Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-20T13:16:55.219032Z digest=sha256:95bea9ee01e9ea19672c121238f3b9d38fe1f49d7107d08c20344c9a5236887d

Observation 910ecd22-714f-4d07-943c-c836fad63e04 · inbound

ERTS: Adversarial Robustness Testing of Ethical AI via Semantic Perturbation in a Bounded Consequence Space cites this paper.

ERTS: Adversarial Robustness Testing of Ethical AI via Semantic Perturbation in a Bounded Consequence Space Adversarial Robustness Toolbox v1.0.0

Reference 8

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T15:08:32.581306Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-27T06:44:54.418857Z digest=sha256:37cbec0d966dd603e6094790a92304682bea0436e1be676b5707fb16a2cb9a57

Observation 6b94051c-855b-4816-be82-1429f1d6b92f · inbound

Enhancing Stateful Detection of Adversarial Attacks with Soft-labels' Temporality and Robust Similarity Approximations cites this paper.

Enhancing Stateful Detection of Adversarial Attacks with Soft-labels' Temporality and Robust Similarity Approximations Adversarial Robustness Toolbox v1.0.0

Reference 20

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T07:09:38.820139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-26T13:34:32.092622Z digest=sha256:8f80918b3c7a2c57d75c88d4b89fbab0da9cff32ab54f340787b8429995ad1ea

Observation 5e7baad3-3129-4b90-b69c-7a9bbe0fd8dd · inbound

Cross-Domain Generalization Failure in Lightweight Intrusion Detection Models for IIoT Networks cites this paper.

Cross-Domain Generalization Failure in Lightweight Intrusion Detection Models for IIoT Networks Adversarial Robustness Toolbox v1.0.0

Reference 26

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T11:36:54.745641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-07-02T11:33:50.033400Z digest=sha256:68446aa4e79c71f191b8bcdc7d29c2d479d160c10c98c57ae0a67c9a58ef7319