Paper Citation Record · LEDGER

RobustBench: a standardized adversarial robustness benchmark

As of 4 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 21 inbound Pith citation observations for arXiv:2010.09670.

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

pith.paper-citation-record.v1
2010.09670 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 21 of 21 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00

measured 21 of 21 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T23:52:40.329981Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-10T06:15:00.866473Z

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 41fe5854-3659-4944-9632-a7a5a8c0fb75 · inbound

Unsolved Problems in ML Safety cites this paper.

Unsolved Problems in ML Safety RobustBench: a standardized adversarial robustness benchmark

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-05-16T20:45:27.578375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 3eeffd4e-6a49-4f00-bfc4-678661658901 · inbound

Language Guided Adversarial Purification cites this paper.

Language Guided Adversarial Purification RobustBench: a standardized adversarial robustness benchmark

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-24T06:49:02.031154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 06abe48c-bd9b-4ad9-8e05-be2212aad3c2 · inbound

SmoothLLM: Defending Large Language Models Against Jailbreaking Attacks cites this paper.

SmoothLLM: Defending Large Language Models Against Jailbreaking Attacks RobustBench: a standardized adversarial robustness benchmark

Reference 43

Resolution: verified exact; arxiv_id, observed 2026-05-14T17:11:00.836163Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation e36b9acd-94d9-4ba4-b31b-9215b7c91db8 · inbound

LLM-Safety Evaluations Lack Robustness cites this paper.

LLM-Safety Evaluations Lack Robustness RobustBench: a standardized adversarial robustness benchmark

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-23T01:27:21.369647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation d2accc3c-5ebb-447c-8d4e-1e1c4d0280c3 · inbound

Contrastive Residual Energy Test-time Adaptation cites this paper.

Contrastive Residual Energy Test-time Adaptation RobustBench: a standardized adversarial robustness benchmark

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-19T12:47:17.886500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 0d4ad231-3973-4dce-ad72-6f8e6e600c80 · inbound

How Well Does GPT-4o Understand Vision? Evaluating Multimodal Foundation Models on Standard Computer Vision Tasks cites this paper.

How Well Does GPT-4o Understand Vision? Evaluating Multimodal Foundation Models on Standard Computer Vision Tasks RobustBench: a standardized adversarial robustness benchmark

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-19T05:57:08.095871Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 8c76d597-7b76-4d26-ae18-5bad78f5d46c · inbound

Sparse Autoencoders are Capable LLM Jailbreak Mitigators cites this paper.

Sparse Autoencoders are Capable LLM Jailbreak Mitigators RobustBench: a standardized adversarial robustness benchmark

Reference 844

Resolution: unresolved; no resolver link, observed 2026-08-02T23:52:40.329981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a42c8e5-74e7-4dac-979f-0efc016d0f15 · inbound

Compression as an Adversarial Amplifier Through Decision Space Reduction cites this paper.

Compression as an Adversarial Amplifier Through Decision Space Reduction RobustBench: a standardized adversarial robustness benchmark

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:20:57.730572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 6d1d6b2e-1a12-4eee-adba-82ce6c24af38 · inbound

Adversarial Label Invariant Graph Data Augmentations for Out-of-Distribution Generalization cites this paper.

Adversarial Label Invariant Graph Data Augmentations for Out-of-Distribution Generalization RobustBench: a standardized adversarial robustness benchmark

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-11T07:41:01.640268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 29d9badd-04f7-4783-96cd-7303ad32f154 · inbound

Learning Robustness at Test-Time from a Non-Robust Teacher cites this paper.

Learning Robustness at Test-Time from a Non-Robust Teacher RobustBench: a standardized adversarial robustness benchmark

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-11T10:11:01.138711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 17b27464-2b81-456d-aaeb-8b87d73c75bf · inbound

Beyond Attack Success Rate: A Multi-Metric Evaluation of Adversarial Transferability in Medical Imaging Models cites this paper.

Beyond Attack Success Rate: A Multi-Metric Evaluation of Adversarial Transferability in Medical Imaging Models RobustBench: a standardized adversarial robustness benchmark

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-10T11:05:08.741111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 36246950-974b-4a9c-b44b-eb8dcddef312 · inbound

Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations cites this paper.

Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations RobustBench: a standardized adversarial robustness benchmark

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-11T22:21:49.775695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 5bf49dc7-9ce0-4e08-9cc4-03dca570b9f2 · inbound

Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations cites this paper.

Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations RobustBench: a standardized adversarial robustness benchmark

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-11T00:50:49.859450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 51c0e61f-8208-4b7d-b001-9ee71946dd63 · inbound

Detecting Adversarial Data via Provable Adversarial Noise Amplification cites this paper.

Detecting Adversarial Data via Provable Adversarial Noise Amplification RobustBench: a standardized adversarial robustness benchmark

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-11T16:26:06.039115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation f42ba1c9-f7cf-41cf-8efa-1e4467afbd22 · inbound

Optimality of Sub-network Laplace Approximations: New Results and Methods cites this paper.

Optimality of Sub-network Laplace Approximations: New Results and Methods RobustBench: a standardized adversarial robustness benchmark

Reference 4

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T07:37:16.357130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation b4ff976b-192c-40c3-a385-a13ac790f130 · inbound

Sensitivity as a Double-Edged Sword: A Trade-off Between Discriminability and Adversarial Robustness cites this paper.

Sensitivity as a Double-Edged Sword: A Trade-off Between Discriminability and Adversarial Robustness RobustBench: a standardized adversarial robustness benchmark

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-07-01T22:06:16.368482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 8aec5943-683b-4844-a2a6-8034b9a48061 · 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 RobustBench: a standardized adversarial robustness benchmark

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-07-01T22:26:17.777832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 8889156c-edfe-43ca-b355-3d4c593012ab · inbound

Toward Calibrated, Fair, and accurate Deepfake Detection cites this paper.

Toward Calibrated, Fair, and accurate Deepfake Detection RobustBench: a standardized adversarial robustness benchmark

Reference 277

Resolution: metadata mismatch; arxiv_id, observed 2026-06-28T07:11:45.356052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation b6f084ff-dac2-4ac7-8c52-5cc71819e445 · inbound

Breaking TinyML: Why Quantized Neural Networks Need Domain-Specific Security Analysis cites this paper.

Breaking TinyML: Why Quantized Neural Networks Need Domain-Specific Security Analysis RobustBench: a standardized adversarial robustness benchmark

Reference 12

Resolution: unresolved; no resolver link, observed 2026-07-12T14:06:47.857777Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 30d7d64a-3568-430d-a612-fa09d189d1b0 · inbound

RoAd-RL: A Unified Library and Benchmark for Robust Adversarial Reinforcement Learning cites this paper.

RoAd-RL: A Unified Library and Benchmark for Robust Adversarial Reinforcement Learning RobustBench: a standardized adversarial robustness benchmark

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-06-30T07:04:21.098034Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation bd659a74-5ea1-4918-9be2-ce6a6da2b041 · inbound

SoK: Adversarial Robustness of the Variational Quantum Eigensolver via Red-Teaming cites this paper.

SoK: Adversarial Robustness of the Variational Quantum Eigensolver via Red-Teaming RobustBench: a standardized adversarial robustness benchmark

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-01T12:50:14.253730Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.