Paper Citation Record · LEDGER

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation

As of 8 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 0 inbound Pith citation observations for arXiv:2506.08611.

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

pith.paper-citation-record.v1
2506.08611 v1

Coverage vector

measured 49 of 49 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:12:28.490786Z

measured 49 of 49 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

49 of 49 outbound references displayed

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External citation measurements

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Outbound references

Observation f2ecd90f-cb67-4c58-964c-5ed776503528 · outbound

This paper cites In: ECCV.

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation In: ECCV

Reference 1

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Observation e5d6c05f-11bd-4589-be60-1df9d16aeeea · outbound

This paper cites In: NeurIPS 2020 Workshop on Pre-registration in Machine Learning.

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation In: NeurIPS 2020 Workshop on Pre-registration in Machine Learning

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:12:29.513742Z

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Observation 29163341-3c49-4470-b5db-0b84dbd20fc3 · outbound

This paper cites In: 2017 ieee symposium on security and privacy (sp).

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation In: 2017 ieee symposium on security and privacy (sp)

Reference 3

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This paper cites In: ICML.

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation In: ICML

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:12:29.480464Z

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Observation 73094bdf-6d91-44b1-93f3-fabc885ce680 · outbound

This paper cites In: ICML.

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation In: ICML

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:12:29.463394Z

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Observation cdc5b72e-9ab9-4a75-bfcd-ea2c9d7ce4a1 · outbound

This paper cites In: Proceedings of the IEEE ICCV.

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation In: Proceedings of the IEEE ICCV

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:12:29.325863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4a120d85-5cbf-4f48-9e8e-284781614895 · outbound

This paper cites In: AAAI.

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation In: AAAI

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:12:29.306067Z

Source-reported events for the cited work

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Observation 440453bb-36f1-4241-aa12-a3270d63ee52 · outbound

This paper cites Explaining and Harnessing Adversarial Examples.

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation Explaining and Harnessing Adversarial Examples

Reference 8

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Observation 85d0b676-781f-46da-9a11-3de474cf08c6 · outbound

This paper cites Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples.

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples

Reference 9

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Observation a9eaaab0-1578-4417-a5e6-4dd31b1df3b5 · outbound

This paper cites In: CVPR.

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation In: CVPR

Reference 10

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Observation 3761db27-6083-4acf-8909-c672400139d1 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation Distilling the Knowledge in a Neural Network

Reference 11

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Observation c9cc0990-d26e-4771-a4a5-22cb6421e7e1 · outbound

This paper cites In: CVPR.

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation In: CVPR

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:12:29.270802Z

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Observation ce3caded-4071-40e2-bcae-24e75bff2199 · outbound

This paper cites In: ECCV.

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation In: ECCV

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:12:29.254148Z

Source-reported events for the cited work

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Observation 8c951fb3-d6f2-4c4c-90da-64259e3a8fb5 · outbound

This paper cites TPAMI (2024).

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation TPAMI (2024)

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:12:29.238095Z

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Observation f0619a12-a73c-47d7-9a2c-8053c1e0b397 · outbound

This paper cites Improving Fast Adversarial Training with Prior-Guided Knowledge.

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation Improving Fast Adversarial Training with Prior-Guided Knowledge

Reference 15

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Observation fb2cc24f-4edb-471b-b285-13dc41e14136 · outbound

This paper cites In: CVPR.

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation In: CVPR

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:12:29.221129Z

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Observation c8120ed9-c168-4609-a5f0-8a22d3dcc2d1 · outbound

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Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation Unresolved cited work

Reference 17

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Observation 94840985-0a82-433a-8ea9-c40f60b30db9 · outbound

This paper cites CS 231N7(7), 3 (2015).

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation CS 231N7(7), 3 (2015)

Reference 18

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Observation ebf57047-6934-4e49-827a-b9bdd2a7c93c · outbound

This paper cites DAFA: Distance-Aware Fair Adversarial Training.

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation DAFA: Distance-Aware Fair Adversarial Training

Reference 19

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Observation b1502850-8542-43fb-918b-95e38c98e5e6 · outbound

This paper cites In: AAAI.

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation In: AAAI

Reference 20

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Observation 63cbe341-3f5a-45cd-8075-006250091bae · outbound

This paper cites NeurIPS35, 26230–26241 (2022).

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation NeurIPS35, 26230–26241 (2022)

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:12:29.159448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a0452686-9dfc-4610-9203-ace9ba49da5d · outbound

This paper cites Towards Deep Learning Models Resistant to Adversarial Attacks.

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation Towards Deep Learning Models Resistant to Adversarial Attacks

Reference 22

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Observation 1b7f66fa-037f-4bc3-aadd-fe29d92336b5 · outbound

This paper cites NeurIPS33, 7779–7792 (2020).

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation NeurIPS33, 7779–7792 (2020)

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:12:29.144054Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 22ce6dd9-d32f-4941-b616-ab4f18da2439 · outbound

This paper cites NeurIPS 34, 29935–29948 (2021).

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation NeurIPS 34, 29935–29948 (2021)

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:12:29.128250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b9f388de-fd3f-44a0-ae18-c14ac1544f9a · outbound

This paper cites In: ICML.

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation In: ICML

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:12:29.105028Z

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Observation 8b7c7752-a583-4f50-b4fb-254531d3e9b7 · outbound

This paper cites In: MICCAI.

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation In: MICCAI

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:12:29.086957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 8f50f413-fc6c-4d20-b492-86e52a69927a · outbound

This paper cites Improving Viewpoint Robustness for Visual Recognition via Adversarial Training.

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation Improving Viewpoint Robustness for Visual Recognition via Adversarial Training

Reference 27

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Observation 0ee4164b-3c01-4185-a5e3-85812fd44341 · outbound

This paper cites In: CVPR.

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation In: CVPR

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation cde2d331-ad70-4447-aaf3-d8429d5446ef · outbound

This paper cites Robust Learning Meets Generative Models: Can Proxy Distributions Improve Adversarial Robustness?.

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation Robust Learning Meets Generative Models: Can Proxy Distributions Improve Adversarial Robustness?

Reference 29

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Observation 5c3f2e29-a331-4bbd-bee0-bc64cebcdc4a · outbound

This paper cites In: AAAI.

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation In: AAAI

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:12:29.047260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f84785ed-bc25-47ff-817b-b116770cc412 · outbound

This paper cites In: CVPR.

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation In: CVPR

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:12:29.026935Z

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Observation f2d8bf51-54ea-4c4c-99e5-e715f0cd4f2b · outbound

This paper cites Intriguing properties of neural networks.

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation Intriguing properties of neural networks

Reference 32

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Observation 1b9905d4-d7a1-484e-b044-eba8e6081715 · outbound

This paper cites In: Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining.

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation In: Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:12:29.003527Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7b60fa66-dd3e-4aec-b1f6-7c2691c0d226 · outbound

This paper cites In: International Conference on Learning Representations (2019).

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation In: International Conference on Learning Representations (2019)

Reference 34

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Observation 1093a3e9-07a1-46d9-aff7-4bb597517d29 · outbound

This paper cites TPAMI (2022).

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation TPAMI (2022)

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:12:28.961742Z

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Observation 8e31b4fb-f8d3-4172-a36a-eddf5f6c3610 · outbound

This paper cites TPAMI (2022).

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation TPAMI (2022)

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:12:28.941585Z

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Observation b1467792-5730-42f3-b135-c6e70c48a7b8 · outbound

This paper cites TPAMI (2023).

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation TPAMI (2023)

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:12:28.924341Z

Source-reported events for the cited work

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Observation d6c4743b-59cc-45cc-acc6-d9681486e903 · outbound

This paper cites TPAMI (2024).

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation TPAMI (2024)

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:12:28.906319Z

Source-reported events for the cited work

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Observation 9164238e-8384-4f09-9e04-b3e58b82523c · outbound

This paper cites In: CVPR.

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation In: CVPR

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:12:28.889125Z

Source-reported events for the cited work

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Observation ad2acdb7-538a-4d8c-b517-557c781e7b61 · outbound

This paper cites an unresolved cited work.

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation Unresolved cited work

Reference 40

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Observation 256cf90f-466e-48af-8595-5d94bc77a01c · outbound

This paper cites NeurIPS (2023).

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation NeurIPS (2023)

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:12:28.855034Z

Source-reported events for the cited work

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Observation 373d6e21-3146-4dd9-b123-556ad728d115 · outbound

This paper cites In: ICML.

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation In: ICML

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:12:28.837210Z

Source-reported events for the cited work

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Observation 10c64e0a-597f-48c4-9bab-c9f902a4522a · outbound

This paper cites Wide Residual Networks.

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation Wide Residual Networks

Reference 43

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Observation a70f9156-fa1e-45b3-902c-cc68ef3d4130 · outbound

This paper cites In: ICML.

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation In: ICML

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:12:28.819304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5518d1bc-2ca1-49dd-83a0-b727ba1deca1 · outbound

This paper cites NeurIPS (2024).

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation NeurIPS (2024)

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:12:28.802624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 62ebf378-be1f-402c-8ce1-7de2f87cc899 · outbound

This paper cites TPAMI (01), 1–14 (2024).

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation TPAMI (01), 1–14 (2024)

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:12:28.784899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 773d23b6-d954-44db-b8cd-4db28ee3af2d · outbound

This paper cites In: ECCV.

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation In: ECCV

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:12:28.767512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation cd9d2e20-a206-465c-ad30-c2ca7347c9d1 · outbound

This paper cites Reliable Adversarial Distillation with Unreliable Teachers.

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation Reliable Adversarial Distillation with Unreliable Teachers

Reference 48

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Observation 361a9d9b-af85-4611-b89a-2c717dacb377 · outbound

This paper cites In: ICCV (2021) Shiji Zhaoreceived his B.S.

Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label Distillation In: ICCV (2021) Shiji Zhaoreceived his B.S

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:12:28.750214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Pith citing papers

No inbound Pith citation observations are available.