Paper Citation Record · LEDGER

RobustBench: a standardized adversarial robustness benchmark

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 39 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

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Source: paper_references, paper_reference_links

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 39 of 39 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:37:25.805944Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

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External citation measurements

116
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

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

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+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

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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

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Observation 74a94fbc-cd4e-4400-b2e5-5f70f7b654db · inbound

Sparse patches adversarial attacks via extrapolating point-wise information cites this paper.

Sparse patches adversarial attacks via extrapolating point-wise information RobustBench: a standardized adversarial robustness benchmark

Reference 23

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Observation b582f5f0-8d4b-4c50-8011-dda6da7e4fcf · inbound

Towards Class-wise Robustness Analysis cites this paper.

Towards Class-wise Robustness Analysis RobustBench: a standardized adversarial robustness benchmark

Reference 5

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Observation 04ebe2d0-1d8f-49e5-84ce-c5dcd82fc9e0 · inbound

SPARNet: Continual Test-Time Adaptation via Sample Partitioning Strategy and Anti-Forgetting Regularization cites this paper.

SPARNet: Continual Test-Time Adaptation via Sample Partitioning Strategy and Anti-Forgetting Regularization RobustBench: a standardized adversarial robustness benchmark

Reference 42

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Observation cf925b89-2afb-4ce0-aea3-bff275c56171 · inbound

AI Governance through Markets cites this paper.

AI Governance through Markets RobustBench: a standardized adversarial robustness benchmark

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-10T04:36:43.819611Z

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Observation 78baaa0b-f1c3-41d6-b9e5-daff0bc48d52 · inbound

The Relationship Between Network Similarity and Transferability of Adversarial Attacks cites this paper.

The Relationship Between Network Similarity and Transferability of Adversarial Attacks RobustBench: a standardized adversarial robustness benchmark

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-10T13:39:29.281974Z

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Observation 7ff5a9c0-2136-411a-acb4-4ffc1782b08c · inbound

Boosting Adversarial Robustness and Generalization with Structural Prior cites this paper.

Boosting Adversarial Robustness and Generalization with Structural Prior RobustBench: a standardized adversarial robustness benchmark

Reference 2

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Observation 475c79f6-5f24-4a9a-9b33-9d4f5b94e030 · inbound

Adapting to Evolving Adversaries with Regularized Continual Robust Training cites this paper.

Adapting to Evolving Adversaries with Regularized Continual Robust Training RobustBench: a standardized adversarial robustness benchmark

Reference 2019

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Observation 1596f007-4aa1-4066-9a88-8c96bc8e9316 · inbound

The Science of Evaluating Foundation Models cites this paper.

The Science of Evaluating Foundation Models RobustBench: a standardized adversarial robustness benchmark

Reference 15

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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

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 17cc5e5c-7981-4612-ab13-76f4e549761f · inbound

Evaluating the Vulnerability of ML-Based Ethereum Phishing Detectors to Single-Feature Adversarial Perturbations cites this paper.

Evaluating the Vulnerability of ML-Based Ethereum Phishing Detectors to Single-Feature Adversarial Perturbations RobustBench: a standardized adversarial robustness benchmark

Reference 18

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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

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 696eda56-d550-4301-8ca4-50cfc21805d7 · inbound

Demystifying Adversarial Robustness in Diffusion Models: Compression, Randomness, and Geometry cites this paper.

Demystifying Adversarial Robustness in Diffusion Models: Compression, Randomness, and Geometry RobustBench: a standardized adversarial robustness benchmark

Reference 2020

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Observation 0f2c42a2-a461-4fce-b93b-311dcca73630 · inbound

Monitoring Robustness and Individual Fairness cites this paper.

Monitoring Robustness and Individual Fairness RobustBench: a standardized adversarial robustness benchmark

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T12:10:50.786167Z

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Observation 7de184a8-e368-47da-b86b-4a2b1d77f38c · inbound

A Red Teaming Roadmap Towards System-Level Safety cites this paper.

A Red Teaming Roadmap Towards System-Level Safety RobustBench: a standardized adversarial robustness benchmark

Reference 18

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Observation 9f089809-40f0-4e8d-a037-6d1656a8b0f7 · inbound

On the Domain Robustness of Contrastive Vision-Language Models cites this paper.

On the Domain Robustness of Contrastive Vision-Language Models RobustBench: a standardized adversarial robustness benchmark

Reference 9

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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 2026-08-19T06:32:44.657259+00:00.

Observation 63dab7ad-e1f3-4f4e-8db9-2d2d45c0fab5 · inbound

Glitches in Decision Tree Ensemble Models cites this paper.

Glitches in Decision Tree Ensemble Models RobustBench: a standardized adversarial robustness benchmark

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T16:16:29.450726Z

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Observation 9eb22942-b5af-43d3-b5a6-0ebc5a82022b · inbound

Theoretical Analysis of Relative Errors in Gradient Computations for Adversarial Attacks with CE Loss cites this paper.

Theoretical Analysis of Relative Errors in Gradient Computations for Adversarial Attacks with CE Loss RobustBench: a standardized adversarial robustness benchmark

Reference 34

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Observation 66bb95d7-fc32-4717-a5b0-97bcd3739a6e · inbound

Learn Faster and Remember More: Balancing Exploration and Exploitation for Continual Test-time Adaptation cites this paper.

Learn Faster and Remember More: Balancing Exploration and Exploitation for Continual Test-time Adaptation RobustBench: a standardized adversarial robustness benchmark

Reference 63

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Observation 661f94b1-f2bd-4963-bb0a-3f6b00907f58 · inbound

DCFS: Continual Test-Time Adaptation via Dual Consistency of Feature and Sample cites this paper.

DCFS: Continual Test-Time Adaptation via Dual Consistency of Feature and Sample RobustBench: a standardized adversarial robustness benchmark

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-15T16:48:59.853590Z

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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

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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

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+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

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+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

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+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

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+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 2026-08-19T06:32:44.657259+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

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+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

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+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

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+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

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+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

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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

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+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

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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

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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

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Observation 3d76b5ce-9238-463f-9fbd-b518eda613d7 · inbound

A Convolutional Layer Activation Dimensionality Reduction for Out-of-Distribution and Adversarial Attack Detection Methods cites this paper.

A Convolutional Layer Activation Dimensionality Reduction for Out-of-Distribution and Adversarial Attack Detection Methods RobustBench: a standardized adversarial robustness benchmark

Reference 2021

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