Paper Citation Record · LEDGER

CEAR: Certified Ensemble Adversarial Robustness in DNNs

As of 7 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2606.01437.

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

pith.paper-citation-record.v1
2606.01437 v1

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-28T17:17:44.826139Z

measured 33 of 33 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 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

33 of 33 outbound references displayed

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verified fuzzy0
unresolved32
parse uncertain0
malformed identifier0
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External citation measurements

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Outbound references

Observation 8ad68c64-deda-4ea2-85a1-841b094ae857 · outbound

This paper cites Adversarial example detection for DNN models: A review and experimental comparison.

CEAR: Certified Ensemble Adversarial Robustness in DNNs Adversarial example detection for DNN models: A review and experimental comparison

Reference 1

Resolution: unresolved; no resolver link, observed 2026-06-28T17:17:44.826139Z

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Observation 208baa6f-f8f1-46f4-b469-9f7dc1d466f5 · outbound

This paper cites Intriguing properties of neural networks.

CEAR: Certified Ensemble Adversarial Robustness in DNNs Intriguing properties of neural networks

Reference 2

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Observation 1c1e3ea0-f7ae-4be0-9bc7-e3c0dfda8b2d · outbound

This paper cites Towards evaluating the robustness of neural networks.

CEAR: Certified Ensemble Adversarial Robustness in DNNs Towards evaluating the robustness of neural networks

Reference 3

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Observation 351497bb-0519-4a31-bf97-51810c72946f · outbound

This paper cites Failure Cases Are Better Learned But Boundary Says Sorry: Facilitating Smooth Perception Change for Accuracy-Robustness Trade-Off in Adversarial Training.

CEAR: Certified Ensemble Adversarial Robustness in DNNs Failure Cases Are Better Learned But Boundary Says Sorry: Facilitating Smooth Perception Change for Accuracy-Robustness Trade-Off in Adversarial Training

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-06-28T17:22:25.114443Z

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Observation 8e491188-e09c-40fb-adcc-4ef43eb98abb · outbound

This paper cites Distillation as a defense to adver- sarial perturbations against deep neural networks.

CEAR: Certified Ensemble Adversarial Robustness in DNNs Distillation as a defense to adver- sarial perturbations against deep neural networks

Reference 5

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Observation 56dae159-3178-43cc-aa86-75caa03b9f1c · outbound

This paper cites Sok: Certified robustness for deep neural networks.

CEAR: Certified Ensemble Adversarial Robustness in DNNs Sok: Certified robustness for deep neural networks

Reference 6

Resolution: unresolved; no resolver link, observed 2026-06-28T17:17:44.826139Z

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Observation ed9900c9-6f3d-45a3-91fd-915077271883 · outbound

This paper cites Semidefinite relaxations for certifying ro- bustness to adversarial examples.

CEAR: Certified Ensemble Adversarial Robustness in DNNs Semidefinite relaxations for certifying ro- bustness to adversarial examples

Reference 7

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Observation f297c97e-4b2f-4778-a1c6-253d53495103 · outbound

This paper cites Certified robustness to ad- versarial examples with differential privacy.

CEAR: Certified Ensemble Adversarial Robustness in DNNs Certified robustness to ad- versarial examples with differential privacy

Reference 8

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Observation 973d01c7-e902-4abc-a968-843104c8af0d · outbound

This paper cites Certified adversarial robustness via randomized smoothing.

CEAR: Certified Ensemble Adversarial Robustness in DNNs Certified adversarial robustness via randomized smoothing

Reference 9

Resolution: unresolved; no resolver link, observed 2026-06-28T17:17:44.826139Z

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Observation 955ce8bf-9986-464d-908f-26a3e64e2689 · outbound

This paper cites Adversarial robustness of neural networks from the perspective of lipschitz calculus: A survey.

CEAR: Certified Ensemble Adversarial Robustness in DNNs Adversarial robustness of neural networks from the perspective of lipschitz calculus: A survey

Reference 10

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Observation 78b70051-3ad5-4051-875c-5f8ef10fdc5d · outbound

This paper cites On the Certified Robustness for Ensemble Models and Beyond.

CEAR: Certified Ensemble Adversarial Robustness in DNNs On the Certified Robustness for Ensemble Models and Beyond

Reference 11

Resolution: unresolved; no resolver link, observed 2026-06-28T17:17:44.826139Z

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Observation d5c1d3d0-dc75-434b-91d7-178df0ea8916 · outbound

This paper cites Advanced defensive distillation with ensemble voting and noisy logits.

CEAR: Certified Ensemble Adversarial Robustness in DNNs Advanced defensive distillation with ensemble voting and noisy logits

Reference 12

Resolution: unresolved; no resolver link, observed 2026-06-28T17:17:44.826139Z

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Observation 3fec3c06-2221-47a5-a8c8-0df0baaf0a22 · outbound

This paper cites Diversity supporting robustness: Enhancing adversarial robustness via differentiated ensemble predictions.

CEAR: Certified Ensemble Adversarial Robustness in DNNs Diversity supporting robustness: Enhancing adversarial robustness via differentiated ensemble predictions

Reference 13

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Observation ebf5484b-7771-431e-928f-0d780626996d · outbound

This paper cites Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks.

CEAR: Certified Ensemble Adversarial Robustness in DNNs Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks

Reference 14

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Observation 25559caf-1cfd-4c46-a867-7b52d84b0936 · outbound

This paper cites Obfuscated gradients give a false sense of security: Circumventing defenses to adversarial examples.

CEAR: Certified Ensemble Adversarial Robustness in DNNs Obfuscated gradients give a false sense of security: Circumventing defenses to adversarial examples

Reference 15

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Observation 77eae2d4-c45a-42e6-baf4-3f688cf37f19 · outbound

This paper cites MACER: attack-free and scalable robust training via maximizing certified radius.

CEAR: Certified Ensemble Adversarial Robustness in DNNs MACER: attack-free and scalable robust training via maximizing certified radius

Reference 16

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Observation e0643d2b-15c1-4dd0-b00e-eb5270c47eb8 · outbound

This paper cites Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers.

CEAR: Certified Ensemble Adversarial Robustness in DNNs Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers

Reference 17

Resolution: unresolved; no resolver link, observed 2026-06-28T17:17:44.826139Z

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Observation fe6d2ba5-de17-4b45-83e5-baee34652f55 · outbound

This paper cites Double-boosted randomized smoothing: A sharp certified defense against adversarial attacks.

CEAR: Certified Ensemble Adversarial Robustness in DNNs Double-boosted randomized smoothing: A sharp certified defense against adversarial attacks

Reference 18

Resolution: unresolved; no resolver link, observed 2026-06-28T17:17:44.826139Z

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Observation e80fd90a-d37e-4afc-8a01-07049f59a0d3 · outbound

This paper cites FASTEN: fast ensemble learning for im- proved adversarial robustness.

CEAR: Certified Ensemble Adversarial Robustness in DNNs FASTEN: fast ensemble learning for im- proved adversarial robustness

Reference 19

Resolution: unresolved; no resolver link, observed 2026-06-28T17:17:44.826139Z

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Observation f0bcbe90-3821-40cc-9083-7b27c7ba7d97 · outbound

This paper cites Enhancing Certified Robustness via Smoothed Weighted Ensembling.

CEAR: Certified Ensemble Adversarial Robustness in DNNs Enhancing Certified Robustness via Smoothed Weighted Ensembling

Reference 20

Resolution: unresolved; no resolver link, observed 2026-06-28T17:17:44.826139Z

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Observation 49f7b9f0-7b8d-4463-9c42-26c7a44e0199 · outbound

This paper cites Dynamically weighted ensemble neural networks for classification.

CEAR: Certified Ensemble Adversarial Robustness in DNNs Dynamically weighted ensemble neural networks for classification

Reference 21

Resolution: unresolved; no resolver link, observed 2026-06-28T17:17:44.826139Z

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Observation ee425b42-7620-4d5a-b90b-a092bd91a36d · outbound

This paper cites Towards certified robustness under label noise.

CEAR: Certified Ensemble Adversarial Robustness in DNNs Towards certified robustness under label noise

Reference 22

Resolution: unresolved; no resolver link, observed 2026-06-28T17:17:44.826139Z

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Observation d97df539-7b78-41fc-b188-751857cb907f · outbound

This paper cites DENL: Diverse Ensemble and Noisy Logits for Improved Robustness of Neural Networks.

CEAR: Certified Ensemble Adversarial Robustness in DNNs DENL: Diverse Ensemble and Noisy Logits for Improved Robustness of Neural Networks

Reference 23

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Observation 5b1ef2f7-af59-4a1e-91b3-d19cce3723ef · outbound

This paper cites On calibration of modern neural networks.

CEAR: Certified Ensemble Adversarial Robustness in DNNs On calibration of modern neural networks

Reference 24

Resolution: unresolved; no resolver link, observed 2026-06-28T17:17:44.826139Z

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Observation e9817d1d-36ae-4850-9367-9b012dcb11df · outbound

This paper cites The limitations of deep learning in adversarial settings.

CEAR: Certified Ensemble Adversarial Robustness in DNNs The limitations of deep learning in adversarial settings

Reference 25

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Observation ac9a3d57-59bc-43fd-ac32-f12c36a49abf · outbound

This paper cites Note on the median of a multivariate distribution.

CEAR: Certified Ensemble Adversarial Robustness in DNNs Note on the median of a multivariate distribution

Reference 26

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Observation a7297483-bfc2-4cef-8ee8-82978b3440a5 · outbound

This paper cites Sur le point pour lequel la somme des distances de n points donnés est mini- mum.

CEAR: Certified Ensemble Adversarial Robustness in DNNs Sur le point pour lequel la somme des distances de n points donnés est mini- mum

Reference 27

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Observation 4985501b-fe96-416d-b36b-f7aef55487ae · outbound

This paper cites LeCun, C.

CEAR: Certified Ensemble Adversarial Robustness in DNNs LeCun, C

Reference 28

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Observation 9819a6f9-6ca3-435e-9f1a-c2d15f216516 · outbound

This paper cites Krizhevsky.Learning Multiple Layers of Features from Tiny Images.

CEAR: Certified Ensemble Adversarial Robustness in DNNs Krizhevsky.Learning Multiple Layers of Features from Tiny Images

Reference 29

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Observation a861884c-b493-4c5a-850d-e770f9297a58 · outbound

This paper cites ImageNet: A Large-Scale Hierarchical Image Database.

CEAR: Certified Ensemble Adversarial Robustness in DNNs ImageNet: A Large-Scale Hierarchical Image Database

Reference 30

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Observation da4d8eeb-a37d-4566-8e58-d8cd314e5e12 · outbound

This paper cites TensorFlow: a system for Large-Scale machine learning.

CEAR: Certified Ensemble Adversarial Robustness in DNNs TensorFlow: a system for Large-Scale machine learning

Reference 31

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Observation e4f51e73-09f5-4d1d-a7c0-76353e17a475 · outbound

This paper cites Gradient-based learning applied to docu- ment recognition.

CEAR: Certified Ensemble Adversarial Robustness in DNNs Gradient-based learning applied to docu- ment recognition

Reference 32

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Observation d3b62692-5ab2-4343-b10f-256b721fb9eb · outbound

This paper cites Deep residual learning for image recognition.

CEAR: Certified Ensemble Adversarial Robustness in DNNs Deep residual learning for image recognition

Reference 33

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Pith citing papers

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