Paper Citation Record · LEDGER

Improving the Robustness/Accuracy Tradeoff Against Adversarial Attacks Using Information Bottleneck Distillation Through Dual Teachers

As of 15 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2607.27737.

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

pith.paper-citation-record.v1
2607.27737 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T02:20:07.518845Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+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

31 of 31 outbound references displayed

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External citation measurements

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Outbound references

Observation 99a18419-155e-456c-b771-ffe2eb07edf1 · outbound

This paper cites Explaining and Harnessing Adversarial Examples,.

Improving the Robustness/Accuracy Tradeoff Against Adversarial Attacks Using Information Bottleneck Distillation Through Dual Teachers Explaining and Harnessing Adversarial Examples,

Reference 1

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Observation ce6a5a81-c65a-4d67-ab98-a72ad436c5e1 · outbound

This paper cites Towards deep learning models resistant to adversarial attacks,.

Improving the Robustness/Accuracy Tradeoff Against Adversarial Attacks Using Information Bottleneck Distillation Through Dual Teachers Towards deep learning models resistant to adversarial attacks,

Reference 2

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Observation 5afa107c-c8b9-4e09-828d-8be59d5fe82f · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Improving the Robustness/Accuracy Tradeoff Against Adversarial Attacks Using Information Bottleneck Distillation Through Dual Teachers Distilling the Knowledge in a Neural Network

Reference 3

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Observation 4c10691e-6131-464c-902e-3e73d122db28 · outbound

This paper cites Distillation as a Defense to Adversarial Perturbations Against Deep Neural Networks,.

Improving the Robustness/Accuracy Tradeoff Against Adversarial Attacks Using Information Bottleneck Distillation Through Dual Teachers Distillation as a Defense to Adversarial Perturbations Against Deep Neural Networks,

Reference 4

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Observation 34a03598-0ffb-473a-9362-5abf6deca64e · outbound

This paper cites The information bottleneck method.

Improving the Robustness/Accuracy Tradeoff Against Adversarial Attacks Using Information Bottleneck Distillation Through Dual Teachers The information bottleneck method

Reference 5

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Observation 1bd8000a-8970-4ff4-8318-5e8d9c44eb1d · outbound

This paper cites Deep Learning and the Information Bottleneck Principle,.

Improving the Robustness/Accuracy Tradeoff Against Adversarial Attacks Using Information Bottleneck Distillation Through Dual Teachers Deep Learning and the Information Bottleneck Principle,

Reference 6

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Observation 6fa712a4-9d19-425f-97d9-445be5280ab0 · outbound

This paper cites On the Information Bottleneck Theory of Deep Learning,.

Improving the Robustness/Accuracy Tradeoff Against Adversarial Attacks Using Information Bottleneck Distillation Through Dual Teachers On the Information Bottleneck Theory of Deep Learning,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-01T02:20:07.443031Z

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Observation 013b5490-35bf-464e-8385-cd2259c938d1 · outbound

This paper cites Improving Adversarial Robustness via Information Bottleneck Distillation,.

Improving the Robustness/Accuracy Tradeoff Against Adversarial Attacks Using Information Bottleneck Distillation Through Dual Teachers Improving Adversarial Robustness via Information Bottleneck Distillation,

Reference 8

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Observation 8b4aebb3-3ca5-4204-8699-6d88513218a0 · outbound

This paper cites Self-Supervised Adversarial Training via Diverse Augmented Queries and Self-Supervised Double Perturbation,.

Improving the Robustness/Accuracy Tradeoff Against Adversarial Attacks Using Information Bottleneck Distillation Through Dual Teachers Self-Supervised Adversarial Training via Diverse Augmented Queries and Self-Supervised Double Perturbation,

Reference 9

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Observation 0bd186e9-7fd2-43cd-ae2d-691ce0dafa5b · outbound

This paper cites Intriguing properties of neural networks,.

Improving the Robustness/Accuracy Tradeoff Against Adversarial Attacks Using Information Bottleneck Distillation Through Dual Teachers Intriguing properties of neural networks,

Reference 10

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Observation 10ec223f-d648-4ab1-87f0-5d8706cd3a76 · outbound

This paper cites Defensive Distillation is Not Robust to Adversarial Examples.

Improving the Robustness/Accuracy Tradeoff Against Adversarial Attacks Using Information Bottleneck Distillation Through Dual Teachers Defensive Distillation is Not Robust to Adversarial Examples

Reference 11

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Observation ffd4d918-f973-49f6-9bd0-512301e164e3 · outbound

This paper cites Adversarial training for free!.

Improving the Robustness/Accuracy Tradeoff Against Adversarial Attacks Using Information Bottleneck Distillation Through Dual Teachers Adversarial training for free!

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-01T02:20:07.460018Z

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Observation 9af72c75-f526-4079-922d-d49e06e6abf8 · outbound

This paper cites FitNets: Hints for thin deep nets,.

Improving the Robustness/Accuracy Tradeoff Against Adversarial Attacks Using Information Bottleneck Distillation Through Dual Teachers FitNets: Hints for thin deep nets,

Reference 13

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Observation 5969d9a5-eb94-4eb6-84d4-84a814906e6b · outbound

This paper cites Deep Variational Information Bottleneck.

Improving the Robustness/Accuracy Tradeoff Against Adversarial Attacks Using Information Bottleneck Distillation Through Dual Teachers Deep Variational Information Bottleneck

Reference 14

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Observation bee6b909-5ab0-439a-b9eb-8026bc13cc2d · outbound

This paper cites The conditional entropy bottleneck,.

Improving the Robustness/Accuracy Tradeoff Against Adversarial Attacks Using Information Bottleneck Distillation Through Dual Teachers The conditional entropy bottleneck,

Reference 15

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Observation 92ead9dd-de13-454e-91ef-1cadca8dc1e6 · outbound

This paper cites The CIFAR-10 dataset,.

Improving the Robustness/Accuracy Tradeoff Against Adversarial Attacks Using Information Bottleneck Distillation Through Dual Teachers The CIFAR-10 dataset,

Reference 16

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Observation ac7e49e7-6da0-44c2-a6dd-818636a0db0c · outbound

This paper cites ResNet-18,.

Improving the Robustness/Accuracy Tradeoff Against Adversarial Attacks Using Information Bottleneck Distillation Through Dual Teachers ResNet-18,

Reference 17

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Observation eb20ce06-f61c-44da-a39d-d64fcbaf6443 · outbound

This paper cites Wide residual networks,.

Improving the Robustness/Accuracy Tradeoff Against Adversarial Attacks Using Information Bottleneck Distillation Through Dual Teachers Wide residual networks,

Reference 18

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Observation 3e78ed89-ce2d-435c-954c-402953a1001f · outbound

This paper cites Theoretically principled trade-off between robustness and accuracy,.

Improving the Robustness/Accuracy Tradeoff Against Adversarial Attacks Using Information Bottleneck Distillation Through Dual Teachers Theoretically principled trade-off between robustness and accuracy,

Reference 19

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Observation 7fd621b8-3cef-40e7-bb0f-09ba63975313 · outbound

This paper cites Towards Evaluating the Robustness of Neural Networks,.

Improving the Robustness/Accuracy Tradeoff Against Adversarial Attacks Using Information Bottleneck Distillation Through Dual Teachers Towards Evaluating the Robustness of Neural Networks,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-01T02:20:07.488250Z

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Observation 0dad2af3-0575-473c-bbc2-8bd0d7550612 · outbound

This paper cites Reliable Evaluation of Adversarial Robustness with an Ensemble of Diverse Parameter-free Attacks,.

Improving the Robustness/Accuracy Tradeoff Against Adversarial Attacks Using Information Bottleneck Distillation Through Dual Teachers Reliable Evaluation of Adversarial Robustness with an Ensemble of Diverse Parameter-free Attacks,

Reference 21

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Observation 8606f3e5-1fb4-4e93-aa5a-8326d19bf981 · outbound

This paper cites Adversarially robust distillation,.

Improving the Robustness/Accuracy Tradeoff Against Adversarial Attacks Using Information Bottleneck Distillation Through Dual Teachers Adversarially robust distillation,

Reference 22

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Observation 9a697a94-e16f-42de-b480-b21d3b20eb80 · outbound

This paper cites Revisiting adversarial robustness distillation: Robust soft labels make student better,.

Improving the Robustness/Accuracy Tradeoff Against Adversarial Attacks Using Information Bottleneck Distillation Through Dual Teachers Revisiting adversarial robustness distillation: Robust soft labels make student better,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-01T02:20:07.497510Z

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Observation 99c5b382-065f-4c71-b9d8-542710033655 · outbound

This paper cites InfoAT: Improving Adversarial Training Using the Information Bottleneck Principle,.

Improving the Robustness/Accuracy Tradeoff Against Adversarial Attacks Using Information Bottleneck Distillation Through Dual Teachers InfoAT: Improving Adversarial Training Using the Information Bottleneck Principle,

Reference 24

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Observation 1d67723c-838e-46a1-a044-c4e563b1b682 · outbound

This paper cites Adversarial Weight Perturbation Helps Robust Generalization,.

Improving the Robustness/Accuracy Tradeoff Against Adversarial Attacks Using Information Bottleneck Distillation Through Dual Teachers Adversarial Weight Perturbation Helps Robust Generalization,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-01T02:20:07.503943Z

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Observation ec6f282e-0fdc-4937-8b9c-5d506c62b6e8 · outbound

This paper cites Revisiting Hilbert–Schmidt Information Bottleneck for Adversarial Robustness,.

Improving the Robustness/Accuracy Tradeoff Against Adversarial Attacks Using Information Bottleneck Distillation Through Dual Teachers Revisiting Hilbert–Schmidt Information Bottleneck for Adversarial Robustness,

Reference 26

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Observation 6c54fbe0-4b84-4eaa-a8a2-ca96d11f10a6 · outbound

This paper cites Conserve-Update-Revise to Cure Generalization and Robustness Trade- off in Adversarial Training,.

Improving the Robustness/Accuracy Tradeoff Against Adversarial Attacks Using Information Bottleneck Distillation Through Dual Teachers Conserve-Update-Revise to Cure Generalization and Robustness Trade- off in Adversarial Training,

Reference 27

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Observation 7c82bca0-3b7d-4c92-95ab-b5235a9463c3 · outbound

This paper cites Mitigating Accuracy-Robustness Trade-off via Balanced Multi-Teacher Adversarial Distillation,.

Improving the Robustness/Accuracy Tradeoff Against Adversarial Attacks Using Information Bottleneck Distillation Through Dual Teachers Mitigating Accuracy-Robustness Trade-off via Balanced Multi-Teacher Adversarial Distillation,

Reference 28

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Observation fdd47469-f2dc-4ab9-a757-31a754b08c5f · outbound

This paper cites Adversarial machine learning: a review of methods, tools, and critical industry sectors,.

Improving the Robustness/Accuracy Tradeoff Against Adversarial Attacks Using Information Bottleneck Distillation Through Dual Teachers Adversarial machine learning: a review of methods, tools, and critical industry sectors,

Reference 29

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Observation 1a65a565-7e09-4a61-b98a-94e8ffb79a2a · outbound

This paper cites A meta-survey of adversarial attacks against artificial intelligence algorithms, including diffusion models,.

Improving the Robustness/Accuracy Tradeoff Against Adversarial Attacks Using Information Bottleneck Distillation Through Dual Teachers A meta-survey of adversarial attacks against artificial intelligence algorithms, including diffusion models,

Reference 30

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Observation 22fed0fc-0742-4dc5-9b83-73044a433e35 · outbound

This paper cites Available: http://www.cs.toronto.edu/ kriz/cifar.html.

Improving the Robustness/Accuracy Tradeoff Against Adversarial Attacks Using Information Bottleneck Distillation Through Dual Teachers Available: http://www.cs.toronto.edu/ kriz/cifar.html

Reference 2009

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Pith citing papers

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