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Paper Citation Record · LEDGER

Defensive Dual Masking for Robust Adversarial Defense

As of 12 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 0 inbound Pith citation observations for arXiv:2412.07078.

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

pith.paper-citation-record.v1
2412.07078 v1

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T19:16:36.730171Z

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+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

14 of 14 outbound references displayed

  • verified exact0
  • verified fuzzy6
  • unresolved8
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation af18e117-ad85-471c-a535-eae2ed249c99 · outbound

This paper cites an unresolved cited work.

Defensive Dual Masking for Robust Adversarial Defense Unresolved cited work

Reference 5

Resolution
unresolved
raw_fallback, observed 2026-08-11T19:16:38.259090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T19:16:36.337170Z digest=sha256:a1dec4396f1ee3910f6a82b455bdb54f8634c4d0e9f4ca65f7a608b4f2db95c6

Observation 47a07965-0e68-406b-9909-62a8ab978cf4 · outbound

This paper cites In Findings of the Association for Computational Linguistics: NAACL 2024, pages 3795–3809, Association for Computational Linguistics, Mexico City, Mexico.

Defensive Dual Masking for Robust Adversarial Defense In Findings of the Association for Computational Linguistics: NAACL 2024, pages 3795–3809, Association for Computational Linguistics, Mexico City, Mexico

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T19:16:38.214744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T19:16:36.374746Z digest=sha256:4c759339946e507c5550ee9ddd66d8be088d466171b06ea8a174bd60e18865bd

Observation b82ea291-5777-4f13-969d-8d8bd666ae15 · outbound

This paper cites In International Conference on Learning Representations.

Defensive Dual Masking for Robust Adversarial Defense In International Conference on Learning Representations

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T19:16:38.145221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T19:16:36.406285Z digest=sha256:59811f51cbd556c6e9d6b381dbe13e3c1421c64d30fdd588b54cb71a1e159c29

Observation d224777c-1640-4c61-8227-d300fd1749d0 · outbound

This paper cites an unresolved cited work.

Defensive Dual Masking for Robust Adversarial Defense Unresolved cited work

Reference 8

Resolution
unresolved
raw_fallback, observed 2026-08-11T19:16:38.029263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T19:16:36.454748Z digest=sha256:ca0bebf32c8a8aa383097fe737694547701e329998150db836c18d4fb4ce308b

Observation f4339145-cc90-4385-9924-a4a9ad4973b7 · outbound

This paper cites Fast Adversarial Training against Textual Adversarial Attacks.

Defensive Dual Masking for Robust Adversarial Defense Fast Adversarial Training against Textual Adversarial Attacks

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-11T19:16:36.504746Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T19:16:36.504746Z digest=sha256:2a868288adcc2ef43c58760d05d4566a3f14ecf052ce48f9a43dab7ef1f03d5c

Observation 9683eea1-30c8-4290-add9-935d2cbb33c6 · outbound

This paper cites ROIC-DM: Robust Text Inference and Classification via Diffusion Model.

Defensive Dual Masking for Robust Adversarial Defense ROIC-DM: Robust Text Inference and Classification via Diffusion Model

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-11T19:16:36.604746Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T19:16:36.604746Z digest=sha256:f1766bc85e0a395c74c8fc380dcc8f30d3bb4548d599267ce88bbf8f69150057

Observation 9bd5d6f4-d8e4-469a-952a-0ef703243d97 · outbound

This paper cites In Findings of the Association for Computational Linguistics: ACL 2023, pages 7891–7906, Association for Computational Linguistics, Toronto, Canada.

Defensive Dual Masking for Robust Adversarial Defense In Findings of the Association for Computational Linguistics: ACL 2023, pages 7891–7906, Association for Computational Linguistics, Toronto, Canada

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T19:16:37.809438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T19:16:36.634745Z digest=sha256:4f5533becc141fe79651b4d7dc6cab0d786135b9f9b12a823ff293e159681df1

Observation 0fbc18c8-b761-4998-b16f-11ff2680399d · outbound

This paper cites an unresolved cited work.

Defensive Dual Masking for Robust Adversarial Defense Unresolved cited work

Reference 14

Resolution
unresolved
raw_fallback, observed 2026-08-11T19:16:37.404749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T19:16:36.730171Z digest=sha256:bb5dbdc78dafbc15306e3410156274d2c2be05ef74f1f8a34f35fe606d5ce27e

Observation e90fa267-78ea-4c5e-8ba8-d43349580180 · outbound

This paper cites In Proceedings of the 28th International Conference on Neural Information Processing Systems - Volume 1, NIPS’15, page 649–657, MIT Press, Cambridge, MA, USA.

Defensive Dual Masking for Robust Adversarial Defense In Proceedings of the 28th International Conference on Neural Information Processing Systems - Volume 1, NIPS’15, page 649–657, MIT Press, Cambridge, MA, USA

Reference 2015

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T19:16:37.634752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T19:16:36.684744Z digest=sha256:3ffae26eada1b485efe1e53eba0d560956e1fe4cc87191a9c7cd2d462383e872

Observation 508de2fc-249b-4dab-8e1a-2886b669a228 · outbound

This paper cites In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 3465–3475, Association for Computational Linguistics, Online.

Defensive Dual Masking for Robust Adversarial Defense In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 3465–3475, Association for Computational Linguistics, Online

Reference 2020

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T19:16:37.914007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T19:16:36.554751Z digest=sha256:0c8cec25e121416ac738b5474a7510bf9c2f6f6a21f0fe20361c6b7933d9e514

Observation 2a85b0f1-a8b1-46dd-89fe-c8a91168cd7e · outbound

This paper cites In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, pages 3248–3258, Association for Computational Linguistics, Online.

Defensive Dual Masking for Robust Adversarial Defense In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, pages 3248–3258, Association for Computational Linguistics, Online

Reference 2021

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T19:16:38.455065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T19:16:36.164747Z digest=sha256:3befcf6324134a21db76e598314ba0b66ef9941a1c40a369fd4388bfae287038

Observation 9b0ffe06-c2e3-436a-a9d7-d3bfaf7f6496 · outbound

This paper cites an unresolved cited work.

Defensive Dual Masking for Robust Adversarial Defense Unresolved cited work

Reference 2022

Resolution
unresolved
raw_fallback, observed 2026-08-11T19:16:38.327525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T19:16:36.204592Z digest=sha256:61976ca400922011334d382a362c7f66d37599c1ff14f1730516a1d6a210587f

Observation 9f8cb12b-95ef-41d3-8d0c-931fdec40464 · outbound

This paper cites an unresolved cited work.

Defensive Dual Masking for Robust Adversarial Defense Unresolved cited work

Reference 2023

Resolution
unresolved
raw_fallback, observed 2026-08-11T19:16:38.282862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T19:16:36.244749Z digest=sha256:2ddd32be7a012c5cf2b913194ce5cc6f7aa3e5717357ff16badf59a0b4497195

Observation 033ce259-4440-4394-9d90-be198244fb3d · outbound

This paper cites DiffuseDef: Improved Robustness to Adversarial Attacks via Iterative Denoising.

Defensive Dual Masking for Robust Adversarial Defense DiffuseDef: Improved Robustness to Adversarial Attacks via Iterative Denoising

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-11T19:16:36.294747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T19:16:36.294747Z digest=sha256:79fea046ed2857dce140e7147113b32d9284a5f843db09843feb246896e0d76e

Pith citing papers

No inbound Pith citation observations are available.