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Paper Citation Record · LEDGER

Privacy-Preserving Federated Averaging with Byzantine Aggregators in Asynchronous Networks

As of 22 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 2026-08-22T06:32:14.747728+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=sha256:109acb7c9195d29b71639452fe203a04046a0099642d81743492a803dd1da6a8

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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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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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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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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source=pdf_text observed=2026-08-03T11:57:34.128238Z digest=sha256:2e11e69089f2454576a3f0e1e5bb944455748562bd8c14d302d727e1d005a2de

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:cf9bc0ccccdd72dadd71a1c6892f97f78ff3bbd8eb547e616379e08519a8e619

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=sha256:9080c45c6890a9c877ad7ece146cf00e943dc6cfd4f8cf351fa637da3ee11d1d

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=sha256:791469069d8e82b8297ac2e82f7c297c6521d7de76ae13c29df69760eb111dbe

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:d653d8e36823c4c1cab82b0cb0d1c12e8278f189ec3c8ce099128e6d2198dd39

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=sha256:287ca77c55e7e1c7c115504b086ecacecf8cd3ffd0ea3fb4d4fa4264978ce89d

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:b01f1811ea09eeb5854f65d27012c3ad99f0f888feeafef047bd87a9985ed1b2

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=sha256:2a866f7b64be96aa1c8417c4cf966de1344ff02b4aa87543aa7b599cba222057

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:d7382db4e25a17e3d8d3bc2b5bead0685f9da76ab77caf5c8f2a267698e357ef

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=sha256:4c57e06584d19197b33992ac6ba0146f074f9aa0cc49582279fdd8bb2b3fb14a

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=sha256:2480f7071b41594e06088e8423d4c977438a20815c19312200844d446f5ae624

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=sha256:1e83c65aa50430509d021e31a3cbc58a19926993d69289955f691530dfdcf03d

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=sha256:9f59c66d59bfb40ebf7fe41cf6664d04a0dbc94836f9434bf5ea06ae9fc8814f

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=sha256:27cfdaaa7d4dbf3e7ef450daf1d695a482fcca4a12dc1317b3dd76ef9f8c748b

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=sha256:0d05d498eac66c7f975a8d4c30cc575fb38630e47c36effe534224049acded51

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=sha256:934abf3069c4f42ba8c77f74afe0a5e1a77c0d563d707522f2b1e4f89b26bf5e

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=sha256:1c7b39bb22232e37e0310ce16c2df4ccd90e6716afd517fa233df6200445be2b

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:c610ee4a470b47b80204e14ef86b9e5a72a5475e3e5a65126e97172ccadc79c6

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=sha256:405e6fbab0c8cc94377e2ac540bdcc2f99d2d3cb5e4d2c0990b1a97ef60f5d11

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=sha256:2df37f301b608a1730e997e26bda48819ed88d542ca24486c89ab2c8b41d4f9b

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=sha256:723b9b3cf45545f9427daef0d284358ca0f9aceb0a35e54aa6b1f16c87e584e9

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=sha256:292073dec71112318a313682bcf651589077696c5ee1bd8e2fadcfa13bb0f36b

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:bc3f1eb378ae006d3a51a5e5e0a82bda551c9c0dd279fd6a5baf5dc99d366977

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=sha256:63c44757ee57879f12c13945ebac4f86d9fc42e6712911667104c7f60e485034

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=sha256:0faafc7d08aae4383baa6d5709df3142e03822a6c6a0148d4e571f52381cd508

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=sha256:925cb3625185d0bd1a9ff6aff28e7ddc392923d5a75eed664b26392c21423966

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=sha256:83f69e59b608d5cad91a546fb78310d3d0531cf258232e10fd25beaa9d061cac

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:d7208710e4f9398a6a6bc6636a527436c220f83e3a7b0895ce9942c9f37cf193

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=sha256:532fd7e159ecdf225b8c3ffd694c3cd4e850c39991add09954e80cbe046eb1db

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:c131ed3dd7919306aa067a4ee68add668454992ee35db29d764653152882405e

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=sha256:78268cbc23df467b9c25eac69ee2131c70f402ac763aa614734604f6dda6f051

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=sha256:32de9e282742aa08c3d53d44a8e3867b7dbae6dc93039d217fb20efdaeba10a7

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=sha256:9513f85905f5b64e19137131174320e5b893f52aeb2973730a1d595efc152ba3

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=sha256:4e7f8fe9185bff5d8d9dd03fca3faac8c7e60e72e01a7f960bb4def8d097046e

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=sha256:143fadfd0612539667608699cf0a1b21bb361a88e59bc6eb3fc6d30bc39b19ce

Pith citing papers

No inbound Pith citation observations are available.