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Paper Citation Record · LEDGER

Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks

As of 15 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2601.04930.

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

pith.paper-citation-record.v1
2601.04930 v2

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T11:57:34.278440Z

measured 43 of 43 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.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

43 of 43 outbound references displayed

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External citation measurements

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Outbound references

Observation 9080e265-2574-48b4-b5f0-ff3736bea012 · outbound

This paper cites Deep Learning with Differential Privacy.

Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks Deep Learning with Differential Privacy

Reference 1

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source=pdf_text observed=2026-08-03T11:57:34.018031Z digest=sha256:a572da33a763f2c8d8f2bb42b449f58c0db18363073eaba8a5a2fe8d6383f401

Observation 821b71a1-c386-4249-86a0-ed6168e08682 · outbound

This paper cites Prio+: Privacy pre- serving aggregate statistics via boolean shares.

Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks Prio+: Privacy pre- serving aggregate statistics via boolean shares

Reference 2

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Observation d551fea1-43c0-4341-8ed2-3f44b21fc14e · outbound

This paper cites Flchain: A blockchain for auditable federated learning with trust and incentive.

Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks Flchain: A blockchain for auditable federated learning with trust and incentive

Reference 3

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Observation 2488c569-235b-480b-9118-a80f8c35aa98 · outbound

This paper cites Secure single-server aggregation with (poly) logarithmic overhead.

Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks Secure single-server aggregation with (poly) logarithmic overhead

Reference 4

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source=pdf_text observed=2026-08-03T11:57:34.105331Z digest=sha256:1f729f5e8bff8300a5481cab847a839f6623e3a90416dde9f1f64c146e4447d7

Observation c8eab9fb-2a86-4858-8b30-6852df15a89c · outbound

This paper cites Asynchronous secure computation.

Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks Asynchronous secure computation

Reference 5

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source=pdf_text observed=2026-08-03T11:57:34.110380Z digest=sha256:0f5fe1f223fbdb509ed51a0f2b9997680822cdcbf272bd51b832e4ee752b5252

Observation 9a0e47e9-8781-4ef0-9a26-be047addec8e · outbound

This paper cites Fantastyc: Blockchain-based federated learning made secure and practical.

Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks Fantastyc: Blockchain-based federated learning made secure and practical

Reference 6

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Observation 7df3e844-26fe-4d6e-a0e6-57e5c3453a96 · outbound

This paper cites Practical Secure Aggregation for Privacy-Preserving Machine Learning.

Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks Practical Secure Aggregation for Privacy-Preserving Machine Learning

Reference 7

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Observation 918dddd8-5de7-492d-9366-d29dd5327a90 · outbound

This paper cites Lightweight, Maliciously Secure Verifiable Function Secret Sharing.

Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks Lightweight, Maliciously Secure Verifiable Function Secret Sharing

Reference 8

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source=pdf_text observed=2026-08-03T11:57:34.124094Z digest=sha256:04e0c63e1e12a937e7ffea17162986fad152f4bcd7f42246ea779850ed86cabd

Observation 49c4d0f5-80ca-4f8d-aeac-c43f87038651 · outbound

This paper cites Practical byzantine fault tolerance.

Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks Practical byzantine fault tolerance

Reference 9

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Observation 5969802c-61e2-4f75-aac1-337b2dff9c5e · outbound

This paper cites Homomorphic Secret Sharing with Veri- fiable Evaluation.

Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks Homomorphic Secret Sharing with Veri- fiable Evaluation

Reference 10

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source=pdf_text observed=2026-08-03T11:57:34.132876Z digest=sha256:635ce7fdb325f5d79445e8088341ff13260d5a09d83cae326d9c90b51f8b6412

Observation 6cbb4692-045d-4bb7-9285-e1e370535812 · outbound

This paper cites Prio: Private, robust, and scalable computation of aggre- gate statistics.

Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks Prio: Private, robust, and scalable computation of aggre- gate statistics

Reference 11

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source=pdf_text observed=2026-08-03T11:57:34.137525Z digest=sha256:dcdab025b312e2cf1415b37f799921c38682e17719b97005e0dd1ac510f2b45c

Observation 73671f2c-c006-470d-b76f-1b8d50024d8f · outbound

This paper cites Cryp- toNets: applying neural networks to encrypted data with high throughput and accuracy.

Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks Cryp- toNets: applying neural networks to encrypted data with high throughput and accuracy

Reference 12

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source=pdf_text observed=2026-08-03T11:57:34.142983Z digest=sha256:8bf8343818afc09ab864520b434560cf8e119d474655835b511469198b2b4eb2

Observation 64cbaa41-2e32-4844-a62f-0ce6829a20a8 · outbound

This paper cites BEAT: Asynchronous BFT Made Practical.

Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks BEAT: Asynchronous BFT Made Practical

Reference 13

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source=pdf_text observed=2026-08-03T11:57:34.147699Z digest=sha256:da936ad53935e9ee3d1b210eaa7a27990af304ce4e56a4b1fd742963805b49ba

Observation 9a87cffe-11c0-4839-8069-9bcd2fbecd45 · outbound

This paper cites Differential Privacy.

Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks Differential Privacy

Reference 14

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source=pdf_text observed=2026-08-03T11:57:34.151971Z digest=sha256:f5d0bbe4551f84eeb1fb1e3939949d06a87d2e14016ad1119d979ffee9e61a96

Observation 3436a4be-399c-4ed2-b3f8-e3b7ef1969da · outbound

This paper cites SEALion: a Framework for Neural Network Inference on Encrypted Data.

Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks SEALion: a Framework for Neural Network Inference on Encrypted Data

Reference 15

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source=pdf_text observed=2026-08-03T11:57:34.156533Z digest=sha256:ee020a69dab2b3c343e829dbd3028d0cd35df0f23c137af1f08051e691947c1b

Observation f2a77421-fcfb-4cf9-bbd2-1e2770f65f7e · outbound

This paper cites Impossibility of Distributed Consensus with One Faulty Process.

Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks Impossibility of Distributed Consensus with One Faulty Process

Reference 16

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source=pdf_text observed=2026-08-03T11:57:34.161345Z digest=sha256:46a9d8ce5a678a1f933aae536db702e32f769d53bea9f0d8b74663cd52b2081e

Observation ce364021-0b8a-4cf9-b95c-ec525c77f02c · outbound

This paper cites Non-IID data in Federated Learning: A Survey with Taxonomy, Metrics, Methods, Frameworks and Future Directions.

Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks Non-IID data in Federated Learning: A Survey with Taxonomy, Metrics, Methods, Frameworks and Future Directions

Reference 17

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source=pdf_text observed=2026-08-03T11:57:34.165445Z digest=sha256:a52ae0520170a97e63f7bb779c647552fdebdf09c847310cb4f95af0c8ed64e8

Observation fd89c0dd-d32e-472c-9616-f5af4505b3a4 · outbound

This paper cites Differential privacy and byzantine resilience in sgd: Do they add up?.

Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks Differential privacy and byzantine resilience in sgd: Do they add up?

Reference 18

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source=pdf_text observed=2026-08-03T11:57:34.170283Z digest=sha256:a35829704e52fa887cbd378f80b6b430545fd4117187bfa8cc9f0c5274f5c5e9

Observation 09577d2c-a471-4614-a1f1-cb20ea38420c · outbound

This paper cites V eri fl: Communication- efficient and fast verifiable aggregation for federated learning.

Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks V eri fl: Communication- efficient and fast verifiable aggregation for federated learning

Reference 19

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source=pdf_text observed=2026-08-03T11:57:34.174831Z digest=sha256:c2ff4de0bad8fba92175b8c917c4897bb2687d9964099231fb2d087a64779adb

Observation 6824cb63-ce02-46d1-94f8-b84823a71d0f · outbound

This paper cites Multi-Agent eXperimenter (MAX).

Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks Multi-Agent eXperimenter (MAX)

Reference 20

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source=pdf_text observed=2026-08-03T11:57:34.179158Z digest=sha256:2132ff47f0044bfb868f7d12ce32de41e430d69873c195465438f2b181ab7bd2

Observation e7cc4f23-87c8-4869-84ec-fce0f720eb41 · outbound

This paper cites Cheater-identifiable homomorphic secret sharing for outsourcing computations.

Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks Cheater-identifiable homomorphic secret sharing for outsourcing computations

Reference 21

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source=pdf_text observed=2026-08-03T11:57:34.183740Z digest=sha256:2f8353c3a3c6d8f340c0fa0a7ff5c9bcae27c7bdc2db444b5fc55702e7ffa1df

Observation ea769c71-026f-4b7f-b793-856d3a3c5ac0 · outbound

This paper cites An Enciphering Scheme Based on a Card Shuffle.

Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks An Enciphering Scheme Based on a Card Shuffle

Reference 22

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source=pdf_text observed=2026-08-03T11:57:34.187851Z digest=sha256:d07db84e178e82541efe11282b8e0ce83a42744e5e5fedb59db299321c8a35f3

Observation e5561006-e577-4ed3-b2aa-c456872fec8e · outbound

This paper cites Constant-Size Commitments to Polynomials and Their Applications.

Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks Constant-Size Commitments to Polynomials and Their Applications

Reference 23

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source=pdf_text observed=2026-08-03T11:57:34.191866Z digest=sha256:97a0c518817e355ddaab92d654da7b37871efe3a4ea2808bdc80569a4b83644d

Observation e44f81b8-4558-4a21-bff7-3bae0f3e6246 · outbound

This paper cites Blockchained on-device federated learning.

Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks Blockchained on-device federated learning

Reference 24

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source=pdf_text observed=2026-08-03T11:57:34.195957Z digest=sha256:d41f8a1514e6e431938abda8b6557e41b02a1210d052c0229679256d9becc41d

Observation 36803cdb-4b40-44bd-aef6-6be5065dfd13 · outbound

This paper cites Byzantine quorum systems.

Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks Byzantine quorum systems

Reference 25

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source=pdf_text observed=2026-08-03T11:57:34.200134Z digest=sha256:c29588cbd9d0d657071a16b8d1adeb52c30a58366dc90b9cd1b435f480563a63

Observation b52b442d-edfe-4a04-84fa-6ed18cc8b14b · outbound

This paper cites Communication- Efficient Learning of Deep Networks from Decentralized Data.

Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks Communication- Efficient Learning of Deep Networks from Decentralized Data

Reference 26

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source=pdf_text observed=2026-08-03T11:57:34.204208Z digest=sha256:2c853cafd784347fa25d706bac95e7f2fc43972be41fb7658786bbe615b41a7b

Observation 2ae3770c-24d6-4e69-bc5c-8a3d6fdf58fe · outbound

This paper cites Collaborative Learning in the Jungle (Decentralized, Byzantine, Heterogeneous, Asynchronous and Nonconvex Learning).

Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks Collaborative Learning in the Jungle (Decentralized, Byzantine, Heterogeneous, Asynchronous and Nonconvex Learning)

Reference 27

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source=pdf_text observed=2026-08-03T11:57:34.208640Z digest=sha256:ea3498e5326757a0b6cb8aa7e6ba6e04675dbfff93e277c40b4538fb1bb18f28

Observation 29dd5c40-93ec-4a0c-b915-765cf0be324a · outbound

This paper cites Genuinely distributed byzantine machine learning.

Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks Genuinely distributed byzantine machine learning

Reference 28

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source=pdf_text observed=2026-08-03T11:57:34.213413Z digest=sha256:4e0b4d47a9c2f376fe0934086fe25a324d5477e5c4c82517ca5d918301ffbf45

Observation be20a9af-b2fc-4a55-8dee-edf860077963 · outbound

This paper cites R´ enyi Differential Privacy.

Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks R´ enyi Differential Privacy

Reference 29

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source=pdf_text observed=2026-08-03T11:57:34.218060Z digest=sha256:882ce803efa0813ebc07227796bc0a5f07de346b415a8317996c9ffbb3ae8e9f

Observation 8999a4d4-4f37-4f49-a5f6-2220ec6a3eab · outbound

This paper cites Non-Interactive and Information-Theoretic Secure Verifiable Secret Sharing.

Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks Non-Interactive and Information-Theoretic Secure Verifiable Secret Sharing

Reference 30

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source=pdf_text observed=2026-08-03T11:57:34.222759Z digest=sha256:8420596bdc6c32e4c5f672830f6e943f119bcabf67ff39ab4e465ca1699215e2

Observation 30c4c26c-85f1-4ecd-bf13-9eca35244396 · outbound

This paper cites Elsa: Secure aggregation for federated learning with malicious actors.

Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks Elsa: Secure aggregation for federated learning with malicious actors

Reference 31

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source=pdf_text observed=2026-08-03T11:57:34.227006Z digest=sha256:e38bb3c079abddcb834052e8b5221ab7dad9ecf5ae2da63ab6916db007b4a2ce

Observation 0e6fbbcf-0418-4c72-8688-a2b9b7e9421f · outbound

This paper cites On lattices, learning with errors, random linear codes, and cryptography.

Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks On lattices, learning with errors, random linear codes, and cryptography

Reference 32

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source=pdf_text observed=2026-08-03T11:57:34.231098Z digest=sha256:342af68dcdffaa362133ce628e9122170e8f3e6b950c63c626b3b45e0e681d74

Observation e3bdfcf0-ed95-413f-84ed-69acb3c8c359 · outbound

This paper cites An accurate, scalable and verifiable protocol for fed- erated differentially private averaging.

Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks An accurate, scalable and verifiable protocol for fed- erated differentially private averaging

Reference 33

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source=pdf_text observed=2026-08-03T11:57:34.235138Z digest=sha256:f0d2a5bb561a8d6246e61b95a8e5e2f24f0e20cbbfbd2a293362c9585591e7d4

Observation f0793a01-7608-4359-b172-b00365848a76 · outbound

This paper cites How to share a secret.

Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks How to share a secret

Reference 34

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source=pdf_text observed=2026-08-03T11:57:34.239926Z digest=sha256:66794689452f30f6b5392206171ac03c23029d35a7d0aefbb45c9705e60112f8

Observation 078dc876-af87-4376-917f-731edac6260f · outbound

This paper cites Biscotti: A blockchain system for private and secure federated learning.

Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks Biscotti: A blockchain system for private and secure federated learning

Reference 35

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source=pdf_text observed=2026-08-03T11:57:34.243977Z digest=sha256:90e9a1177af2e69086f3af055b7c7481c1163105710d4448cc4cce8dac05fcc6

Observation b723d079-d017-4c4a-9328-16d5755841db · outbound

This paper cites Practical threshold signatures.

Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks Practical threshold signatures

Reference 36

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source=pdf_text observed=2026-08-03T11:57:34.248619Z digest=sha256:ffa705264cdc78e7b5dec63558ee38fcceb50296ed3b4954de7bdfbc4c1bfe96

Observation cd160e5c-8d71-452b-a494-04bb77b5be34 · outbound

This paper cites Efficient Differentially Private Secure Aggregation for Federated Learning via Hardness of Learning with Errors.

Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks Efficient Differentially Private Secure Aggregation for Federated Learning via Hardness of Learning with Errors

Reference 37

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source=pdf_text observed=2026-08-03T11:57:34.253246Z digest=sha256:da8516031b0c8b8441dcf344ccecbb2c3fa9596e99ff9d2a20d565e120c33e1c

Observation 174ea9b2-8b04-4466-b5b0-d2119731d335 · outbound

This paper cites A flexible and scalable malicious secure aggregation protocol for federated learning.

Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks A flexible and scalable malicious secure aggregation protocol for federated learning

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-03T11:57:34.257286Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T11:57:34.257286Z digest=sha256:7e58bfa79fc8fb36b461b88d67716ffda7c2c81a885182ecc9b9b8d247a49340

Observation 94d0f93f-04a7-46ab-a3c0-a8a9c158d608 · outbound

This paper cites Sum It Up: Verifiable Additive Homomorphic Secret Sharing.

Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks Sum It Up: Verifiable Additive Homomorphic Secret Sharing

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-03T11:57:34.261491Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T11:57:34.261491Z digest=sha256:dabc1d79d5bf1cbf1fe3b41cd89957a59af77809d0843405d76f190eb9bdc219

Observation 51d04516-2b37-45ee-8c32-edc784b20943 · outbound

This paper cites VerifyNet: Secure and verifiable federated learn- ing.

Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks VerifyNet: Secure and verifiable federated learn- ing

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-03T11:57:34.266414Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T11:57:34.266414Z digest=sha256:38b3a956e3f59400ca45d767c0609923caae697840b40c38fb1836312c53fea7

Observation 2d359de4-37fc-4bb4-ab6d-1c13c4a323ab · outbound

This paper cites Privacy risk in machine learning: Ana- lyzing the connection to overfitting.

Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks Privacy risk in machine learning: Ana- lyzing the connection to overfitting

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-03T11:57:34.270370Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T11:57:34.270370Z digest=sha256:887d9f648d332862dfa4de46ddc7711df3ab4d0e23c75fa4388b9145713e5b01

Observation 9c361cdf-6361-42b9-b66c-6d285d54bf1d · outbound

This paper cites See through gradients: Image batch recovery via gradinversion.

Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks See through gradients: Image batch recovery via gradinversion

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-03T11:57:34.274568Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T11:57:34.274568Z digest=sha256:a836276a1b26fc0f4a0d369ab6667b6d5983b15d06680d5b6d1bf86da35041ca

Observation 8a295311-bdae-4a4f-8d28-1a6cb00d7957 · outbound

This paper cites Deep leakage from gradients.

Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks Deep leakage from gradients

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-03T11:57:34.278440Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T11:57:34.278440Z digest=sha256:6332b6b37000f44936433c507547c8e02942cc6cca0d91415f613b0fec0fde76

Pith citing papers

No inbound Pith citation observations are available.