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Paper Citation Record · LEDGER

Towards Trustworthy Federated Learning with Untrusted Participants

As of 16 August 2026, this Paper Citation Record lists 74 of 74 outbound references and 1 inbound Pith citation observation for arXiv:2505.01874.

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

pith.paper-citation-record.v1
2505.01874 v2

Coverage vector

measured 74 of 74 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:21:00.547075Z

measured 75 of 75 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:15:44.535038Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-07T12:15:46.518013Z

Reference resolution

74 of 74 outbound references displayed

  • verified exact1
  • verified fuzzy46
  • unresolved26
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 25896afc-4893-4e0b-88df-83adf7ae211e · outbound

This paper cites write newline.

Towards Trustworthy Federated Learning with Untrusted Participants write newline

Reference 1

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unresolved
no resolver link, observed 2026-08-16T04:21:00.249698Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:21:00.249698Z digest=sha256:faf239ef95d833e7058fe38c13bb671853866a876b8efdb85ad8bbafb24f8716

Observation c6696cf4-2cb4-4d59-88e0-f4f58088f541 · outbound

This paper cites Robust testing and estimation under manipulation attacks.

Towards Trustworthy Federated Learning with Untrusted Participants Robust testing and estimation under manipulation attacks

Reference 2

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verified fuzzy
raw_fallback, observed 2026-08-16T04:21:02.052739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.255891Z digest=sha256:3c7f2dfe54ea77bbba3322b4480fb6bc15f77351e25bacf1a0400e5f922f19d2

Observation f3061f2b-5da5-41a0-8b3a-f4c74fc325c2 · outbound

This paper cites T., Yu, F.

Towards Trustworthy Federated Learning with Untrusted Participants T., Yu, F

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:21:02.040616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.260441Z digest=sha256:91216e054603bb6519c4f165714b6f53713e6ff5ddd447257d330024a9401abc

Observation 33f01c2d-e2e3-4988-906e-18cc08866f07 · outbound

This paper cites K., Tankala, P., Venkat, P., and Zhang, F.

Towards Trustworthy Federated Learning with Untrusted Participants K., Tankala, P., Venkat, P., and Zhang, F

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:21:02.028467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.264229Z digest=sha256:fa5485cffbe18f67532f7478baccb9fc756bc7fa0bc896599c3b147b1a7732a3

Observation 645e7aae-b3e4-4b01-b60d-29dc59071714 · outbound

This paper cites B yzantine-resilient non-convex stochastic gradient descent.

Towards Trustworthy Federated Learning with Untrusted Participants B yzantine-resilient non-convex stochastic gradient descent

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:21:02.015836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.267936Z digest=sha256:8c05bf262fd9ee64048d297c5fa0bc26a41b989e867da1df349220fe1a513dde

Observation 35c1e86c-b89f-4b6c-b861-0fe031a22ac6 · outbound

This paper cites Fixing by mixing: A recipe for optimal byzantine ml under heterogeneity.

Towards Trustworthy Federated Learning with Untrusted Participants Fixing by mixing: A recipe for optimal byzantine ml under heterogeneity

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:21:02.000776Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.271875Z digest=sha256:31ac2789da0edfd0971b7ca7b466dff0fb6ad8010e21869a4548698c732b62cf

Observation 09f2e326-fb50-4e2c-ba44-091012142c9a · outbound

This paper cites Robust distributed learning: Tight error bounds and breakdown point under data heterogeneity.

Towards Trustworthy Federated Learning with Untrusted Participants Robust distributed learning: Tight error bounds and breakdown point under data heterogeneity

Reference 7

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verified fuzzy
raw_fallback, observed 2026-08-16T04:21:01.984858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.275533Z digest=sha256:a196f361f3ec0f6f1a078d7861dd01fcb90311e6bc74b38789a10ea9bb1f5e8c

Observation 9b454248-2b98-4201-ad2f-465709dfae41 · outbound

This paper cites On the privacy-robustness-utility trilemma in distributed learning.

Towards Trustworthy Federated Learning with Untrusted Participants On the privacy-robustness-utility trilemma in distributed learning

Reference 8

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verified fuzzy
raw_fallback, observed 2026-08-16T04:21:01.970487Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.279443Z digest=sha256:46f6b92990c772072f10431c094782c38ffed7238350660ae5f41e8b1c49af4d

Observation dbb81095-8bc9-4962-bd73-b34565ff44b2 · outbound

This paper cites The privacy power of correlated noise in decentralized learning.

Towards Trustworthy Federated Learning with Untrusted Participants The privacy power of correlated noise in decentralized learning

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:21:01.956657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.283008Z digest=sha256:4a5b67b7a3f10046fe916c7f9622527f9d017aeb219d75a4f860f58086a057a1

Observation bc7858e0-b30e-4a40-9c8d-a6aad80534a7 · outbound

This paper cites A little is enough: Circumventing defenses for distributed learning.

Towards Trustworthy Federated Learning with Untrusted Participants A little is enough: Circumventing defenses for distributed learning

Reference 10

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raw_fallback, observed 2026-08-16T04:21:01.942050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.286292Z digest=sha256:a5ea282e9035fff79daf0bdfd20ff6a2d70d1e12c39a200d1c28119fc33d403c

Observation 8ab1fba5-2e45-4bed-9f99-e2fc930068e8 · outbound

This paper cites Private empirical risk minimization: Efficient algorithms and tight error bounds.

Towards Trustworthy Federated Learning with Untrusted Participants Private empirical risk minimization: Efficient algorithms and tight error bounds

Reference 11

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no resolver link, observed 2026-08-16T04:21:00.289893Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:21:00.289893Z digest=sha256:48a9b921c73a8b4a007df513ece03c3b07b3ea990c7cfe65581f46639f34691d

Observation aceee6f6-9133-4a65-b881-7d1dd9faacbe · outbound

This paper cites and Tsitsiklis, J.

Towards Trustworthy Federated Learning with Untrusted Participants and Tsitsiklis, J

Reference 12

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raw_fallback, observed 2026-08-16T04:21:01.918924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.293251Z digest=sha256:86bcdcec3cdfd837874b9f32f970e3d0973f981844a42909e1f7cf3604f7e166

Observation 77260611-0386-47ab-a6a0-4e537255f950 · outbound

This paper cites M., Guerraoui, R., and Stainer, J.

Towards Trustworthy Federated Learning with Untrusted Participants M., Guerraoui, R., and Stainer, J

Reference 13

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raw_fallback, observed 2026-08-16T04:21:01.904559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.296615Z digest=sha256:869ceb38d94643bb0b9fce015791d944b56e0c61e479b9b269ca2bc1874e7573

Observation be90e061-2754-403d-96ab-2ef4d9fb00b0 · outbound

This paper cites B., Patel, S., Ramage, D., Segal, A., and Seth, K.

Towards Trustworthy Federated Learning with Untrusted Participants B., Patel, S., Ramage, D., Segal, A., and Seth, K

Reference 14

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unresolved
no resolver link, observed 2026-08-16T04:21:00.299964Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:21:00.299964Z digest=sha256:91a517b49342bb0260717648b70542ab3ac9f0569993602bf1119098c6599a5e

Observation 8afa0318-6c0f-4f82-beac-92936ff84989 · outbound

This paper cites Distributed statistical machine learning in adversarial settings: B yzantine gradient descent.

Towards Trustworthy Federated Learning with Untrusted Participants Distributed statistical machine learning in adversarial settings: B yzantine gradient descent

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:21:01.881064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.303149Z digest=sha256:7cc54c298d27cb4d60b990f9c8228d40d09c470f2c76366e8cf58e40c4844d9d

Observation 3e4f45eb-f94d-4830-aa44-c6bd475e2a58 · outbound

This paper cites Distributed differential privacy via shuffling.

Towards Trustworthy Federated Learning with Untrusted Participants Distributed differential privacy via shuffling

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:21:01.866213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.307159Z digest=sha256:2e585fed6db86b13665348a7b05fd0a922c7ce426235417c4fd882e21e5a4bbb

Observation d53ac042-b492-4a36-a711-375544037693 · outbound

This paper cites Manipulation attacks in local differential privacy.

Towards Trustworthy Federated Learning with Untrusted Participants Manipulation attacks in local differential privacy

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:21:01.850960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.311111Z digest=sha256:de2a774e7b0c3753e468582bd7dbeb699fa177b308707d1895fb5eab5a893ca9

Observation 539e8232-01ff-4a45-8d19-c32b44d87489 · outbound

This paper cites Towards practical homomorphic aggregation in byzantine-resilient distributed learning.

Towards Trustworthy Federated Learning with Untrusted Participants Towards practical homomorphic aggregation in byzantine-resilient distributed learning

Reference 18

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no resolver link, observed 2026-08-16T04:21:00.315102Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:21:00.315102Z digest=sha256:f8d0ac5d81d5340507b52559b1fb55b5fc3f34f2ea3fd9daa26580609caddd23

Observation aaed6396-0268-4332-9eae-0bd5aac4fd83 · outbound

This paper cites Differential Privacy-enabled Federated Learning for Sensitive Health Data.

Towards Trustworthy Federated Learning with Untrusted Participants Differential Privacy-enabled Federated Learning for Sensitive Health Data

Reference 19

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unresolved
no resolver link, observed 2026-08-16T04:21:00.319408Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:21:00.319408Z digest=sha256:b7a481eca821fe89c2bc1fa5b0e7ce6ff705b9638df2ee61582abffbc3fa9c78

Observation 1b84d317-0992-4c33-9cb2-9f13c3fc75a1 · outbound

This paper cites and Boneh, D.

Towards Trustworthy Federated Learning with Untrusted Participants and Boneh, D

Reference 20

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verified fuzzy
raw_fallback, observed 2026-08-16T04:21:01.837262Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.324225Z digest=sha256:f6650bed0f426f8bf70f0251d12a9184e5de16e4bfe3406c8092cbb8cbcc1f52

Observation c8472cdd-5adc-4d4d-b9a5-4d713540f12e · outbound

This paper cites a., Senior, A., Tucker, P., Yang, K., Le, Q., and Ng, A.

Towards Trustworthy Federated Learning with Untrusted Participants a., Senior, A., Tucker, P., Yang, K., Le, Q., and Ng, A

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:21:01.824484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.328348Z digest=sha256:1ba10ddd45c5b1427beec4c19d74bfd529b5e6c7b7d02211cdc4b2514b782371

Observation 95c92eb9-1f61-4c67-a5da-fbba7e3d54f6 · outbound

This paper cites M., Li, J., Moitra, A., and Stewart, A.

Towards Trustworthy Federated Learning with Untrusted Participants M., Li, J., Moitra, A., and Stewart, A

Reference 22

Resolution
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raw_fallback, observed 2026-08-16T04:21:01.811063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.332577Z digest=sha256:a97b5f738a7129fe0e29148052ee585e3c3d608f305d6e0d76bd81f7f56c2bf9

Observation 631c8814-5e99-4bc0-a133-623d3233c829 · outbound

This paper cites C., Jordan, M.

Towards Trustworthy Federated Learning with Untrusted Participants C., Jordan, M

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:21:01.797568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.336658Z digest=sha256:742214b13565c703f4ba99cc20e0761c0097e2c408f063df6fbbfee5ffa167a2

Observation 7161a1db-d429-4f29-8a0e-fc664783ca99 · outbound

This paper cites C., Jordan, M.

Towards Trustworthy Federated Learning with Untrusted Participants C., Jordan, M

Reference 24

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no resolver link, observed 2026-08-16T04:21:00.340906Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:21:00.340906Z digest=sha256:8e2c7e01e37524ceaa41b0e8b524a390e01d2d12b668b8913c6a56569baeab86

Observation 0030b0ce-eee2-429a-80a5-3d2ae6155b3e · outbound

This paper cites Amplification by shuffling: From local to central differential privacy via anonymity.

Towards Trustworthy Federated Learning with Untrusted Participants Amplification by shuffling: From local to central differential privacy via anonymity

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:21:01.773836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.345469Z digest=sha256:1eb8ec4160b15868b6483d8e6373bd673d6d4c527fcacd5ca903cfc63bd83b60

Observation d929e3c6-f0f2-437f-8921-b5c6f21ab45e · outbound

This paper cites B yzantine machine learning made easy by resilient averaging of momentums.

Towards Trustworthy Federated Learning with Untrusted Participants B yzantine machine learning made easy by resilient averaging of momentums

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:21:01.759053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.350052Z digest=sha256:58ff7388091fab6768b0ff0fe936eee47059f87622f5071fdd3e8fd9cd4590b5

Observation e13bff53-132c-45ab-b9c6-8133a6ac3b13 · outbound

This paper cites Distributed robust learning, 2015.

Towards Trustworthy Federated Learning with Untrusted Participants Distributed robust learning, 2015

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:21:01.744074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.354534Z digest=sha256:e9e29d4e4400bcdb6ff354b90fac1b4473c561f27f1c45793b667e769a5e5796

Observation 5746a607-e5ae-4bc2-ab23-d3fb30a85ba8 · outbound

This paper cites Model inversion attacks that exploit confidence information and basic countermeasures.

Towards Trustworthy Federated Learning with Untrusted Participants Model inversion attacks that exploit confidence information and basic countermeasures

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-16T04:21:00.358847Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:21:00.358847Z digest=sha256:ac57c12c99897c347608b24fc3c376694376bb503ec18b46235f307927b77fed

Observation e86b333a-d8dd-44d4-8c50-63f901ce446f · outbound

This paper cites R \'e nyi divergence measures for commonly used univariate continuous distributions.

Towards Trustworthy Federated Learning with Untrusted Participants R \'e nyi divergence measures for commonly used univariate continuous distributions

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:21:01.730039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.363078Z digest=sha256:b41f62bdbff1d0c452986c9e4d5dd836bc587f3f6a428603c1ce9b3ff86848b9

Observation f21be6d1-2087-4d2d-82cf-a35ece9f04ea · outbound

This paper cites DP-BREM: Differentially-Private and Byzantine-Robust Federated Learning with Client Momentum.

Towards Trustworthy Federated Learning with Untrusted Participants DP-BREM: Differentially-Private and Byzantine-Robust Federated Learning with Client Momentum

Reference 30

Resolution
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no resolver link, observed 2026-08-16T04:21:00.367137Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:21:00.367137Z digest=sha256:cf3619b6ead33d8184b46e4ba30a570f75c2298ad4b2cfc04f78fcc1e049b8b9

Observation e82f1e3d-6a75-48d8-b5d1-502e172a2c07 · outbound

This paper cites an unresolved cited work.

Towards Trustworthy Federated Learning with Untrusted Participants Unresolved cited work

Reference 31

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no resolver link, observed 2026-08-16T04:21:00.371772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:21:00.371772Z digest=sha256:a2b1fe5bb778fd7b442f58e2872fbf563bce3a67a900dec9c15f6ddb5a85a896

Observation a5bb5cf2-619f-40ed-b5c5-533ad5b3d1b9 · outbound

This paper cites Deep residual learning for image recognition.

Towards Trustworthy Federated Learning with Untrusted Participants Deep residual learning for image recognition

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-16T04:21:00.375963Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:21:00.375963Z digest=sha256:dd902315422a9436219b61d2156bbc2e4599c56beaedbdf2fdb08e546ea467a6

Observation c8d2b670-9769-4d53-8824-c11c7c599041 · outbound

This paper cites Deep models under the gan: Information leakage from collaborative deep learning.

Towards Trustworthy Federated Learning with Untrusted Participants Deep models under the gan: Information leakage from collaborative deep learning

Reference 33

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unresolved
no resolver link, observed 2026-08-16T04:21:00.380134Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:21:00.380134Z digest=sha256:44c383a48af1e40ed1e4a0bc003ae6abfd0b3c85123709b1a6e025cc52faea0d

Observation af0283c0-e540-48bb-93c5-de24be782a3d · outbound

This paper cites B., Kamath, G., and Majid, M.

Towards Trustworthy Federated Learning with Untrusted Participants B., Kamath, G., and Majid, M

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:21:01.706397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.384258Z digest=sha256:9c49bd2e12324675ded4bc4e313d62f21e45d6e5de1b4218775763eb3318f679

Observation 3f3679d2-7dc9-48f5-af15-9206db660f1e · outbound

This paper cites Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification.

Towards Trustworthy Federated Learning with Untrusted Participants Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification

Reference 35

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unresolved
no resolver link, observed 2026-08-16T04:21:00.388632Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:21:00.388632Z digest=sha256:4bcd4f38ad30b78c118c1d74117933145869ffed39b4e18d522bebdb142fcd54

Observation 4a6a2931-5dc4-4077-8b8b-dc910d9bf267 · outbound

This paper cites Personalized federated learning with differential privacy.

Towards Trustworthy Federated Learning with Untrusted Participants Personalized federated learning with differential privacy

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:21:01.692654Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.393299Z digest=sha256:920a3988a1c09cffa7b6226fbbac6762d776a572b20f94445d00acc025f0bb55

Observation 5f602c0a-7f4e-4f21-b33b-02993242d5e4 · outbound

This paper cites M., Sarwate, A.

Towards Trustworthy Federated Learning with Untrusted Participants M., Sarwate, A

Reference 37

Resolution
metadata mismatch
raw_fallback, observed 2026-08-16T04:21:01.008382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.397532Z digest=sha256:1454541c57aa227d81072f5bb228802617ac0242e8f4c508d2aa9423ea523552

Observation 458393b5-ee35-49a1-9b94-ef267107cad4 · outbound

This paper cites Distributed learning without distress: Privacy-preserving empirical risk minimization.

Towards Trustworthy Federated Learning with Untrusted Participants Distributed learning without distress: Privacy-preserving empirical risk minimization

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:21:01.678914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.401922Z digest=sha256:8c97f2fa05a54d1150367151a9308786995864c5dc211abc4f1d6a84d2904dfc

Observation bd308d2b-b50d-4773-8a9c-b9e0d7e89056 · outbound

This paper cites B., Avent, B., Bellet, A., Bennis, M., Bhagoji, A.

Towards Trustworthy Federated Learning with Untrusted Participants B., Avent, B., Bellet, A., Bennis, M., Bhagoji, A

Reference 39

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unresolved
no resolver link, observed 2026-08-16T04:21:00.406495Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:21:00.406495Z digest=sha256:eac49d4b4d4dc4d035853c229011bceb7f94234d40449970d90f5834881cb087

Observation d1c9645c-7912-4195-9ed1-2c494219e22c · outbound

This paper cites A., Makowski, M.

Towards Trustworthy Federated Learning with Untrusted Participants A., Makowski, M

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:21:01.653835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.410535Z digest=sha256:76bd7293658a65ffa0c3a29a8bacf9632f1e4c63a545fb84dcb3a1b3a4ebf16c

Observation 2d2c5d7f-81f2-48a4-b48f-aeb202b13dcb · outbound

This paper cites Linear convergence of gradient and proximal-gradient methods under the polyak- ojasiewicz condition.

Towards Trustworthy Federated Learning with Untrusted Participants Linear convergence of gradient and proximal-gradient methods under the polyak- ojasiewicz condition

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:21:01.639660Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.414869Z digest=sha256:c8806ad224c8984b96cb1ecb515aaa66b74f8f824eb365ca477e2b83da8670a4

Observation 3ff06b01-e254-434b-bc7b-e7ae12d8640d · outbound

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

Towards Trustworthy Federated Learning with Untrusted Participants P., Kale, S., Mohri, M., Reddi, S., Stich, S., and Suresh, A

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:21:01.626926Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.418975Z digest=sha256:695eb63ac45ba494fbdb1b5cbedb843e8d9031bda379abfe045db215775bb80d

Observation e8a50679-36b1-40d8-ab10-96901cd4688f · outbound

This paper cites P., He, L., and Jaggi, M.

Towards Trustworthy Federated Learning with Untrusted Participants P., He, L., and Jaggi, M

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:21:01.614673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.423076Z digest=sha256:b94049ab5e428241a42cc4f54e1eee038269cbd92a1ab29191c7e09d1e219b6a

Observation d84edfd7-fd2e-4335-8c7d-9647e11b709e · outbound

This paper cites P., He, L., and Jaggi, M.

Towards Trustworthy Federated Learning with Untrusted Participants P., He, L., and Jaggi, M

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:21:01.600195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.427135Z digest=sha256:8bb3eeb58cb2a2e6387ba391ffb94b52759f5b0e31a7af751056b71d22b07e16

Observation b82143f9-ba59-4134-865e-c4e1e25f58a3 · outbound

This paper cites P., Lee, H.

Towards Trustworthy Federated Learning with Untrusted Participants P., Lee, H

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-16T04:21:00.430827Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:21:00.430827Z digest=sha256:63e51da7de3f4379921ed35123aeee88180753e4945c8b6a3c4fe7a4adbbc879

Observation 5b88d548-e7e5-4e1c-ac15-d98cec71b013 · outbound

This paper cites The B yzantine generals problem.

Towards Trustworthy Federated Learning with Untrusted Participants The B yzantine generals problem

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-16T04:21:00.434369Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:21:00.434369Z digest=sha256:19e64f324272e600edf614533ae5b2d4110d49138a93994ec13d442c5f96c3d4

Observation 7613655c-6e20-46d5-84e3-d65c903a3638 · outbound

This paper cites and Cortes, C.

Towards Trustworthy Federated Learning with Untrusted Participants and Cortes, C

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:21:01.577556Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.438004Z digest=sha256:915678d9c9567187e81e882998130f9d6cd9a6fd730ca6628b46c18852bba28a

Observation f7f1d325-351c-4b63-91d1-473e80c61a36 · outbound

This paper cites Robust and differentially private mean estimation.

Towards Trustworthy Federated Learning with Untrusted Participants Robust and differentially private mean estimation

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:21:01.563288Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.441573Z digest=sha256:82c67182321dbd74a9ef67c606eaea14341453f3d155b3402e2d34f179c14f87

Observation a4b28c01-0231-4082-8eaa-d8185a469935 · outbound

This paper cites Differentially private B yzantine-robust federated learning.

Towards Trustworthy Federated Learning with Untrusted Participants Differentially private B yzantine-robust federated learning

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:21:01.548479Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.444934Z digest=sha256:bfb5e1055bcb7ec8e4bc052735fbfafc13465b38640f00d0bb8f3b7a50750c24

Observation 07b23795-2292-4aa3-8073-05a8c158ca32 · outbound

This paper cites D., and Shmatikov, V.

Towards Trustworthy Federated Learning with Untrusted Participants D., and Shmatikov, V

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-16T04:21:00.448453Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:21:00.448453Z digest=sha256:1a754a4e2789ae92a5313348d65087314ece07575f2c169239646addf3f5b201

Observation bf9e9843-9f85-4f99-b7f0-87a9d648ad0d · outbound

This paper cites R \'e nyi differential privacy.

Towards Trustworthy Federated Learning with Untrusted Participants R \'e nyi differential privacy

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-16T04:21:00.452221Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:21:00.452221Z digest=sha256:9c67fc57d6f735a91c97d07a565eb660812b7e39f9185614a3f76ad1e64ff8e4

Observation 6adae7b2-9d8d-43b8-aa1a-3905c85e47c8 · outbound

This paper cites an unresolved cited work.

Towards Trustworthy Federated Learning with Untrusted Participants Unresolved cited work

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-16T04:21:00.455644Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:21:00.455644Z digest=sha256:8fa07931f218ca9b02077ca4b947d91280524fed7ccd7853667676d37eb67172

Observation b512f7c9-9986-4723-8d00-587b7c77c7d7 · outbound

This paper cites Differentially private federated learning on heterogeneous data.

Towards Trustworthy Federated Learning with Untrusted Participants Differentially private federated learning on heterogeneous data

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:21:01.516448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.459020Z digest=sha256:7f15f5071c139d9dd68c9c5b857cda0ede89c8c8fe977c277e52ee0af367d18f

Observation 6debd4fd-f4b7-4cfc-8cd3-b4e4e39f39e2 · outbound

This paper cites Lecture notes: Statistics, optimization and algorithms in high dimension, 2020.

Towards Trustworthy Federated Learning with Untrusted Participants Lecture notes: Statistics, optimization and algorithms in high dimension, 2020

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:21:01.500820Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.462983Z digest=sha256:89414fff629124954058c4e428050acb53cbef270cd213561ff0aea1f8120845

Observation bbcd3a2c-b97a-4971-9f73-2800e7ab4076 · outbound

This paper cites T., Aono, Y., Hayashi, T., Wang, L., and Moriai, S.

Towards Trustworthy Federated Learning with Untrusted Participants T., Aono, Y., Hayashi, T., Wang, L., and Moriai, S

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:21:01.487034Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.467333Z digest=sha256:f60e0dc7d2fe6387541c9a3b940c19fb690e5af8174d517edc05cdf7c8c32ab4

Observation e5b4dc14-84c5-40ac-a089-03420d40e864 · outbound

This paper cites an unresolved cited work.

Towards Trustworthy Federated Learning with Untrusted Participants Unresolved cited work

Reference 56

Resolution
unresolved
raw_fallback, observed 2026-08-16T04:21:01.473626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.471465Z digest=sha256:3a03ccb57c50f5379d7b68ccab061f1ca14271a77d47f32140c0ac2b193e70bf

Observation 6cedb57a-b0a0-4046-b024-23844cb2f034 · outbound

This paper cites and H \"u tter, J.-C.

Towards Trustworthy Federated Learning with Untrusted Participants and H \"u tter, J.-C

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:21:01.460354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.475645Z digest=sha256:74f014b7b3c27707d8759069be542cf1a6fca1a47c7fa925f0f490ae6f9037c8

Observation 2370fae9-69ee-4ce3-bd7e-51e9d692c4df · outbound

This paper cites An accurate, scalable and verifiable protocol for federated differentially private averaging.

Towards Trustworthy Federated Learning with Untrusted Participants An accurate, scalable and verifiable protocol for federated differentially private averaging

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:21:01.446167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.479832Z digest=sha256:e0f4eb087b7cfa84cf31e888b586974f48ff21d5844233c796406bcd8b340e94

Observation e6a848f2-6138-4d72-975e-934da7be7d33 · outbound

This paper cites How to share a secret.

Towards Trustworthy Federated Learning with Untrusted Participants How to share a secret

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-16T04:21:00.484189Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:21:00.484189Z digest=sha256:399428476ee478049c3371e22f51971a6ed70039ae14b3f56235f259458fe589

Observation fe0715e7-12cc-484c-a923-ef771eeea1c3 · outbound

This paper cites Membership Inference Attacks against Machine Learning Models.

Towards Trustworthy Federated Learning with Untrusted Participants Membership Inference Attacks against Machine Learning Models

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-16T04:21:00.488254Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:21:00.488254Z digest=sha256:2bf3fd4054cc8a1d0802a741ade2d4e095d7c3d3197604b7c1296f0a1985bcc3

Observation 2632eb07-1470-4830-8d5f-7234f66bbab6 · outbound

This paper cites Resilience: A criterion for learning in the presence of arbitrary outliers.

Towards Trustworthy Federated Learning with Untrusted Participants Resilience: A criterion for learning in the presence of arbitrary outliers

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:21:01.412390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.492952Z digest=sha256:90a677650a555c22cdfa4e5e8f3007af158ebc913b4a95597c3ca797b35443c5

Observation 9c5cc2da-6e0e-4c7f-b291-47aae463d49f · outbound

This paper cites Introduction to the non-asymptotic analysis of random matrices.

Towards Trustworthy Federated Learning with Untrusted Participants Introduction to the non-asymptotic analysis of random matrices

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-16T04:21:00.496985Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:21:00.496985Z digest=sha256:175ceb837a776d1c44c733dd875c2739d3ed92d662277b4520ec2db7fbc3219f

Observation 3d05033b-3031-4f2d-a511-ae4800665825 · outbound

This paper cites Beyond inferring class representatives: User-level privacy leakage from federated learning.

Towards Trustworthy Federated Learning with Untrusted Participants Beyond inferring class representatives: User-level privacy leakage from federated learning

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-16T04:21:00.501823Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:21:00.501823Z digest=sha256:485eeb2d12a74f23a3e5d787a088145405ef126d8c953767308bf555d6e66aae

Observation da12245c-c25a-4b63-a853-bb3102e1889d · outbound

This paper cites Distributed Non-Convex Optimization with One-Bit Compressors on Heterogeneous Data: Efficient and Resilient Algorithms.

Towards Trustworthy Federated Learning with Untrusted Participants Distributed Non-Convex Optimization with One-Bit Compressors on Heterogeneous Data: Efficient and Resilient Algorithms

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-16T04:21:00.505987Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:21:00.505987Z digest=sha256:f75991d74910ffb9c11667f1cd26cf85c008a0e2ed4012383a27783f300691cc

Observation 62cade4a-07ed-43d6-afba-325e5590da82 · outbound

This paper cites Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms.

Towards Trustworthy Federated Learning with Untrusted Participants Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms

Reference 65

Resolution
unresolved
no resolver link, observed 2026-08-16T04:21:00.510505Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:21:00.510505Z digest=sha256:e83d560e7c3c4f9fbfab97a67aa148fe506c0d2da8d58e377ab9d8e6d2afc7a3

Observation 69040a6b-4f98-47d9-b5ad-bd123d053ea8 · outbound

This paper cites Generalized B yzantine-tolerant sgd.

Towards Trustworthy Federated Learning with Untrusted Participants Generalized B yzantine-tolerant sgd

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:21:01.400146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.514822Z digest=sha256:526ed6094a9a6365c0a28e279f009bf8bb5a7d6a3c2644219f8bde797b0c7863

Observation 21cb9a30-b70c-4dc0-9e7e-6f7ff3c8b447 · outbound

This paper cites Fall of empires: Breaking byzantine-tolerant sgd by inner product manipulation.

Towards Trustworthy Federated Learning with Untrusted Participants Fall of empires: Breaking byzantine-tolerant sgd by inner product manipulation

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:21:01.385193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.519771Z digest=sha256:575b36514b7e70862ee81d518cb4a6b7328af42189a0c75afc5d8cd7c483d8f7

Observation f202fe13-f029-40d6-9eea-10fa578994f7 · outbound

This paper cites Unraveling the connections between privacy and certified robustness in federated learning against poisoning attacks.

Towards Trustworthy Federated Learning with Untrusted Participants Unraveling the connections between privacy and certified robustness in federated learning against poisoning attacks

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:21:01.370138Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.524016Z digest=sha256:afc103331fdc2473c10f2286924b214996eac3a8ddbcf119a73c396c2c870551

Observation fe30d771-680d-441d-a217-093ab2148ec6 · outbound

This paper cites B yzantine-robust distributed learning: Towards optimal statistical rates.

Towards Trustworthy Federated Learning with Untrusted Participants B yzantine-robust distributed learning: Towards optimal statistical rates

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:21:01.355689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.528015Z digest=sha256:bc884aee135e317916abdbf7a8109d8ac8196918eb979c66164312a2ca3920e7

Observation c27c6d70-14a4-4f42-bff6-9ab15aba4889 · outbound

This paper cites Opacus: User-Friendly Differential Privacy Library in PyTorch.

Towards Trustworthy Federated Learning with Untrusted Participants Opacus: User-Friendly Differential Privacy Library in PyTorch

Reference 70

Resolution
unresolved
no resolver link, observed 2026-08-16T04:21:00.532103Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:21:00.532103Z digest=sha256:32f01513686436147e6b87c9979f7a3c3b423e73d39fb93ec0f2965e55db33a0

Observation 9f38fa0c-4c3d-4f79-b505-34a7878e0a97 · outbound

This paper cites BatchCrypt : Efficient homomorphic encryption for Cross-Silo federated learning.

Towards Trustworthy Federated Learning with Untrusted Participants BatchCrypt : Efficient homomorphic encryption for Cross-Silo federated learning

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:21:01.341593Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.536474Z digest=sha256:c2040505f5d7728462b9de4f6ce37657bd69882c7e06b5fb8639f10f7497b971

Observation 62964878-98c8-4ebb-ba70-812874d0dd25 · outbound

This paper cites Robust estimation via generalized quasi-gradients.

Towards Trustworthy Federated Learning with Untrusted Participants Robust estimation via generalized quasi-gradients

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:21:01.327515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.540025Z digest=sha256:0742de8c2209e22b7cc8eb1606584270c9a7b08eaa5d67a8d9c4198a07a4b873

Observation 0606d51a-86cb-41e3-a76b-82a6ec1580d0 · outbound

This paper cites and Ling, Q.

Towards Trustworthy Federated Learning with Untrusted Participants and Ling, Q

Reference 73

Resolution
verified exact
doi, observed 2026-08-16T04:21:00.582307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.543622Z digest=sha256:4eaf3ac5e8e00b562f8155b7df3ae724f99bb2c6999a7bb00f5b29649a518604

Observation b0318781-333a-4373-83f6-769ae224c20e · outbound

This paper cites Deep leakage from gradients.

Towards Trustworthy Federated Learning with Untrusted Participants Deep leakage from gradients

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:21:01.310990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-16T04:21:00.547075Z digest=sha256:e6a328a59506d9fde487ad4766e8e6d8119040fce1a06b2ed315597d65e266b1

Pith citing papers

Observation 36ffd402-0f88-447a-9ef9-d1aa524a184e · inbound

ByzFL: Research Framework for Robust Federated Learning cites this paper.

ByzFL: Research Framework for Robust Federated Learning Towards Trustworthy Federated Learning with Untrusted Participants

Reference 2024

Resolution
verified exact
local_arxiv, observed 2026-08-07T12:15:46.623048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-07T12:15:44.535038Z digest=sha256:65dcf4af03f4565e17b970db659caf012ac57bb1cfb553fa1ab6152ca29e40da