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Paper Citation Record · LEDGER

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning?

As of 14 August 2026, this Paper Citation Record lists 66 of 66 outbound references and 0 inbound Pith citation observations for arXiv:2412.08282.

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

pith.paper-citation-record.v1
2412.08282 v2

Coverage vector

measured 66 of 66 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T18:06:13.131265Z

measured 66 of 66 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+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

66 of 66 outbound references displayed

  • verified exact5
  • verified fuzzy2
  • unresolved59
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8c3643b7-fd96-4c50-9959-0ba25b89b327 · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 1

Resolution
unresolved
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation edc02912-94e1-4ee0-a727-a00c5c5da67f · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 2

Resolution
unresolved
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation a50d547d-ad20-4f49-8c9e-41fbaa039d2a · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 3

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:06:14.852080Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation fadeb268-3665-4285-9634-fd66f6fd1421 · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 4

Resolution
unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T18:06:12.751430Z digest=sha256:a3101cc7a867b2feb0c58528ebda3f0a16f90baa360d7b0ff51a52131b756f08

Observation 32030c41-b12d-4460-936e-0744af1e7433 · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 5

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:06:14.820538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 4e36834c-f322-4619-ab2b-c2595fea1f98 · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 6

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:06:14.800407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation a2eba34d-0df7-4fba-887a-e5f9fd208b75 · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-11T18:06:12.766617Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T18:06:12.766617Z digest=sha256:e456d8bfbb9b108e5e1495b40f3af3d7e2c171483f0d6fada23635d9f11a6759

Observation 4729e470-f395-478d-add1-e86d37bdfc9b · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 8

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:06:12.770702Z digest=sha256:48b353cafbd7d6bbf1794dad1fd4ca551b6b56405cf80a8e1b70710ab8b49db5

Observation d22b6055-ca36-422a-9816-b09a796950b2 · outbound

This paper cites Stability and Generalization in Free Adversarial Training.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Stability and Generalization in Free Adversarial Training

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-08-11T18:06:13.873220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 1165fcd0-4ebc-4311-8f32-c17a56ffcec4 · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 10

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unresolved
no resolver link, observed 2026-08-11T18:06:12.784159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation f8de682f-ffff-46f0-b27c-58b47499ba9f · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 11

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 65ba8e51-c039-45dd-9dab-4b7210e47d1b · outbound

This paper cites C.; Bartlett, P.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? C.; Bartlett, P

Reference 12

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:06:12.793983Z digest=sha256:47a8c8ab693546b8b29d9b41449a4ef1b0d5409f34cb3b9ceb4462642c61796b

Observation fd2cf41a-3ac2-4a04-ba3a-d1632c9bf08a · outbound

This paper cites Explaining and Harnessing Adversarial Examples.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Explaining and Harnessing Adversarial Examples

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-11T18:06:12.803058Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 8d47d7a5-e5cd-43ab-a5eb-97609ff3829e · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 14

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:06:12.809447Z digest=sha256:687ebaa2ba1b389564a9d57b53b113957c8e61a80dc9af8933b1270fd4f41143

Observation 45cca800-ab6d-4f09-b2ef-9748ac87e2cd · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 15

Resolution
unresolved
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:06:12.815851Z digest=sha256:8fda368b5236bea33be88a7247a43bc21a11c0b8091f3a79164a0632c3407136

Observation 0ae4cd6e-6aa8-4a56-8440-a1627c9f5c57 · outbound

This paper cites Federated Robustness Propagation: Sharing Robustness in Heterogeneous Federated Learning.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Federated Robustness Propagation: Sharing Robustness in Heterogeneous Federated Learning

Reference 16

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:06:12.822215Z digest=sha256:5b8c4c2387d4d37cfe6eeb3cfdcda5be97170d3eb46a9695ea9874d75ad6921d

Observation 8e37ca4e-6588-4777-afd2-1f9ffb837f4a · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 6778cf26-b596-44b4-9858-6fd7ba7c24e7 · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 48edae6a-7b36-4bf8-8f69-c4d3886a2284 · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation c6a15500-fed3-4a2c-bea8-7e1ac0fd4b47 · outbound

This paper cites P.; Kale, S.; Mohri, M.; Reddi, S.; Stich, S.; and Suresh, A.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? P.; Kale, S.; Mohri, M.; Reddi, S.; Stich, S.; and Suresh, A

Reference 20

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 59d39f57-9f9d-4f76-86b5-4a487c187059 · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 5a20bfee-02a4-44d5-ae5f-c7b9a4006d04 · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 2bbddb2a-58dc-4970-9739-e769f3489345 · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 23

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 527ecf30-f11c-4b75-a631-88b0c61e78d6 · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 24

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 2b09ce4a-83cc-48aa-8980-a1337de7c701 · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 25

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 3d6f5ba9-8510-4994-80c6-8603e0f7ed9a · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 26

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation a2b339ed-6dd9-4ac8-afeb-bc3124c645af · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 27

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation ea3337ca-9855-4e60-a569-44f4275f41e0 · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation d9bfb39d-3705-46aa-82aa-5fb7cb31bc07 · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation e00de9c8-7362-4a39-b4f1-e9a8575daedf · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation d80f5ac9-3b72-4420-8eba-5bfc83eabdc9 · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation dd4325f9-bcb4-4cb7-b6d8-1dc6c795cd68 · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 32

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 2cd9e4a1-bcf5-42ae-bb45-18f04224c449 · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 33

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 38943f22-f389-471c-8fe5-efae0dcfe45f · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 34

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation a016a232-9b39-4b40-856c-e280171f00ce · outbound

This paper cites Y.; et al.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Y.; et al

Reference 35

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T18:06:12.950533Z digest=sha256:a038ffd497d4cf514f4fc2967efba18689418fe432313f90eba8481a69ff69e4

Observation 12b9da84-b3d7-44ea-b6dc-ce5871f08d0f · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 36

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:06:14.260375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:06:12.955665Z digest=sha256:a324c5fcb471cf5d8a3a58bdd4d2c94999cd67981f451236cc947df4a44eade9

Observation 092dce66-0c79-420a-a410-938983b53104 · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 37

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:06:14.241137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:06:12.960393Z digest=sha256:2d02c521be6a48c4582211d5493a9646249edd016303e503fd38fcc62ecfe5c3

Observation aa107136-365f-400e-bb5f-ed40cc60d20e · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 38

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:06:14.216811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:06:12.964908Z digest=sha256:871f2265a4c135363af0e18ff9825e24991aa392ca33ac22418a2d8bb6b9bdc5

Observation a48a5dc1-9318-411b-ba27-1cbc1ec65cb7 · outbound

This paper cites Adaptive Federated Optimization.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Adaptive Federated Optimization

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-11T18:06:12.969570Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T18:06:12.969570Z digest=sha256:b079d6f696ae3abd5fcb223595564b1c7b6a704bf39731879fb7484de5df69ae

Observation ed1be2f0-8d8a-40d8-8084-277b7af8acdd · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 40

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:06:14.193267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:06:12.974683Z digest=sha256:d0e9f6e71e5973aa0e4afce1fc7b3d43e469e80acf7c3ec47b97ea379dea8bb2

Observation b79aedc7-79f9-42f0-9e2b-986ce58dae96 · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 41

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:06:14.176161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:06:12.980394Z digest=sha256:5b37445fb3671cbf3e416224d91e1f0fe0bda57b70240f71356b0971e1d36710

Observation f4032e61-7ca7-487b-aba8-8bb5251027ec · outbound

This paper cites Learning while Respecting Privacy and Robustness to Distributional Uncertainties and Adversarial Data.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Learning while Respecting Privacy and Robustness to Distributional Uncertainties and Adversarial Data

Reference 42

Resolution
verified exact
local_arxiv, observed 2026-08-11T18:06:13.650941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:06:12.986007Z digest=sha256:aeb041ca13738a2ac9ca5ea01dc95c27e245e700cd9b0da5bf46e83ead3695e7

Observation 4ce9a904-2aea-4b40-b517-f1825bb32887 · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 43

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:06:14.155947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:06:12.991989Z digest=sha256:d0198ff07491d8563839ef79781fcaefbd77c7f9db21fdcd22feef8391d642bd

Observation 6ad3986b-0f95-41e4-9cbb-468f387df028 · outbound

This paper cites Adversarial training in communication constrained federated learning.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Adversarial training in communication constrained federated learning

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-11T18:06:12.997128Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T18:06:12.997128Z digest=sha256:91a432990d286ad9e31c28c4dd1143f5b648a387aa3a71182c209827015d071a

Observation 69201047-44c6-4d6e-ad8d-dc21563967ec · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 45

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:06:14.140416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:06:13.001893Z digest=sha256:ade3a43238bc3dafc5a82621cfe5f0b00e5921de154b76f519c54b2f798272ad

Observation ecd66324-4550-440a-bd6c-ff32ac075a7e · outbound

This paper cites SAT: Improving Adversarial Training via Curriculum-Based Loss Smoothing.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? SAT: Improving Adversarial Training via Curriculum-Based Loss Smoothing

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-11T18:06:13.006615Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T18:06:13.006615Z digest=sha256:663a2702a13515e61b4cb7247e312ccfe80c17347e2f4072ea3353b4ece438fd

Observation 1f279a58-2ada-482a-b9a4-324df45c1968 · outbound

This paper cites Understanding Generalization of Federated Learning via Stability: Heterogeneity Matters.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Understanding Generalization of Federated Learning via Stability: Heterogeneity Matters

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-11T18:06:13.012111Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T18:06:13.012111Z digest=sha256:efe6d1f1b0e02ef15d39c4d937710b400ff5f4c91b1735ee25fabc524ef245fa

Observation 68771c90-ad4d-4e91-abcb-01f276488f25 · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 48

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:06:14.124916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:06:13.017645Z digest=sha256:ec9bc1606fd6ee6a32d201b2c8c312aa38cd66b4876749e91925c3fdc0d53670

Observation b5b97116-8a27-49cf-be95-ef6b2f1e7316 · outbound

This paper cites Intriguing properties of neural networks.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Intriguing properties of neural networks

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-11T18:06:13.022328Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T18:06:13.022328Z digest=sha256:e819372680ed22ecb9f9087ef2aa20317fd32e3587c53af80c50a8dd1c6933d1

Observation 4418daa9-1f7a-4945-a2bb-11c0ea8a0b1d · outbound

This paper cites A.; ter Braak, C.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? A.; ter Braak, C

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:06:14.108146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:06:13.027874Z digest=sha256:8a94ab2d90a012d0cbb1b561e26f9787d2c47c58564271da60df0b609aacb629

Observation 80be4bd5-f606-4f77-ad38-67be797a309c · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 51

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:06:14.090452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:06:13.032553Z digest=sha256:06800285ca11daa3d8defabd193641c6251b188edb2928e3a7acc0743be74a2d

Observation 5041dcf8-30ef-45d0-95e6-9ad9a1a0c9c8 · outbound

This paper cites Generalization Guarantees of Gradient Descent for Multi-Layer Neural Networks.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Generalization Guarantees of Gradient Descent for Multi-Layer Neural Networks

Reference 52

Resolution
verified exact
local_arxiv, observed 2026-08-11T18:06:13.259522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:06:13.038843Z digest=sha256:a0c2f5c5d29f98fd15efd6dab12f98898773795231ca89e1bb7293eb0b61fa00

Observation d0fbdc97-e13c-4e59-9325-17e831f14631 · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 53

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:06:14.067441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:06:13.045718Z digest=sha256:6f432b344a55e1c8926b6cf0961c23386bee0eecaaebeee8f633c7e5b8f9efdb

Observation 44448a00-1c8c-4353-9b35-67bead58dd15 · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 54

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:06:14.049050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:06:13.052025Z digest=sha256:e31e544ae90d9d62c1fe9d31adfc6d3c7151227b2f215cba617e55f583ceb2c3

Observation dcb2077a-8445-4e85-bdb7-c49f314e2e1d · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 55

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:06:14.025326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:06:13.060989Z digest=sha256:a173aa1ed4ae3d83220098cbd4f7b680a3cd9609921dcdad42d5ccbee77d13f9

Observation 74f33b9b-fedd-4ff8-8e5d-79ff8df74399 · outbound

This paper cites Smooth Adversarial Training.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Smooth Adversarial Training

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-11T18:06:13.070414Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T18:06:13.070414Z digest=sha256:0dfbf65c3f5ccd1e21f95f8ffb5123330945acf6edbc56ca8df942e355ecbc1d

Observation ad1bccbc-8952-4720-968d-f459cfc4f7f1 · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 57

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:06:14.009790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:06:13.075826Z digest=sha256:091a6723b9b2a67a8f4a0ec5296680cf42ceb4e093a96b1986ba4b4b61c8e7b7

Observation cb72c315-fa80-4c87-9ce2-74d365bbfd2e · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 58

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:06:13.988126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:06:13.081533Z digest=sha256:8c57b54fa810af42908ec6353701ddeb61deb2cc05caf6438390064b5de3a283

Observation 62258bd2-305a-48f9-8d97-bd4c1074029d · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 59

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:06:13.971003Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:06:13.086828Z digest=sha256:5dbc2b2a59ab543dda95da8907bd56817d5418f7b0247a80e9055ec23ae3eef7

Observation e69e2407-1fa2-4e63-b97f-73613d493420 · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 60

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:06:13.952148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:06:13.093132Z digest=sha256:be60dd0738193f0b6d95e15c0826e8cf50c5120c640825cface535cf4b8e9567

Observation c323ab1e-0781-4f14-8b51-eb71b3ae8f98 · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 61

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:06:13.934661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:06:13.101912Z digest=sha256:2bf044ae49851fec76373df3ed4730870175e3ed58fee432c7a57d3d58d99210

Observation a2841c8a-b3d1-461f-a3bd-54a01c83d30a · outbound

This paper cites an unresolved cited work.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Unresolved cited work

Reference 62

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:06:13.915672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:06:13.107088Z digest=sha256:a58c613b3e99c0e9b5b81b7b14356305e320bde2a3599e7f109ae6ffc5add5d8

Observation 5c7d4d90-0dbc-40ad-97e1-c49c72cba934 · outbound

This paper cites Combating Exacerbated Heterogeneity for Robust Models in Federated Learning.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Combating Exacerbated Heterogeneity for Robust Models in Federated Learning

Reference 63

Resolution
verified exact
local_arxiv, observed 2026-08-11T18:06:13.201876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:06:13.111731Z digest=sha256:db21c8d13f3300628fb63b4ada3592639e4846d58ae1f2c093160459919cd798

Observation b04ebc99-aad5-4aaa-817f-57c1e7e2378a · outbound

This paper cites FAT: Federated Adversarial Training.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? FAT: Federated Adversarial Training

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-11T18:06:13.118900Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T18:06:13.118900Z digest=sha256:57fecdb3668180c764edd32b0ad5e80c453e3a13c8ad2270cc1467efa46b30bc

Observation 0fcd0509-2e59-409a-a505-15c6404492e0 · outbound

This paper cites , " * write output.state after.block = add.period write newline.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? , " * write output.state after.block = add.period write newline

Reference 65

Resolution
unresolved
no resolver link, observed 2026-08-11T18:06:13.125945Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T18:06:13.125945Z digest=sha256:3901b7497f94dc07709205bab2e838397e9fddf330eea9f927e310011f0d77e8

Observation 6e230e02-5358-4ec6-8efd-1f3062d56f4e · outbound

This paper cites write newline.

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? write newline

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-11T18:06:13.131265Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T18:06:13.131265Z digest=sha256:5dd670b2b931449edadbc39f6ad710b628a66a3745f9aeb389fad85d34953c6f

Pith citing papers

No inbound Pith citation observations are available.