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Paper Citation Record · LEDGER

An End-to-End Encrypted Neural Network for Gradient Updates Transmission in Federated Learning

As of 17 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 0 inbound Pith citation observations for arXiv:1908.08340.

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

pith.paper-citation-record.v1
1908.08340 v1

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T11:45:05.514888Z

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

13 of 13 outbound references displayed

  • verified exact0
  • verified fuzzy7
  • unresolved6
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1d5bf583-0bf0-41cd-a6a1-a341e2b0c643 · outbound

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

An End-to-End Encrypted Neural Network for Gradient Updates Transmission in Federated Learning Communication-Efficient Learning of Deep Networks from Decentralized Data

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-14T11:45:05.452586Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T11:45:05.452586Z digest=sha256:10e34ae2ef7151b5d2d3b8c23dd7f185890fa4f758bc3c228baf5683bcfaf120

Observation 5a5caa44-10d7-4e3a-b7ca-c1ad2ce00ef6 · outbound

This paper cites Privacy-preserving deep learning,.

An End-to-End Encrypted Neural Network for Gradient Updates Transmission in Federated Learning Privacy-preserving deep learning,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:45:05.756874Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-14T11:45:05.458556Z digest=sha256:4cec0e2bdc6a9fe9e924a4acfdc77fbbef2df9241dd7d395756829cd781cbae1

Observation 087ef3fc-0521-41db-937e-f1562ddb3f08 · outbound

This paper cites 1 -bit stochastic gradient descent and application to data-parallel distributed trai ning of speech DNNs,.

An End-to-End Encrypted Neural Network for Gradient Updates Transmission in Federated Learning 1 -bit stochastic gradient descent and application to data-parallel distributed trai ning of speech DNNs,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:45:05.739778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-14T11:45:05.463716Z digest=sha256:dd5c0fb387c5f235681bc3d19a0c0a74154d72521448ce8cc910bb3a8d976491

Observation f1b0b927-f44f-42cf-b50b-a7580c794efb · outbound

This paper cites TernGrad: Ternary Gradients to Reduce Communication in Distributed Deep Learning.

An End-to-End Encrypted Neural Network for Gradient Updates Transmission in Federated Learning TernGrad: Ternary Gradients to Reduce Communication in Distributed Deep Learning

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-14T11:45:05.468807Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T11:45:05.468807Z digest=sha256:afd3befe042017f1cac150ddf69e8a39a1fda3b310170f7af12c6f2118912cf7

Observation 059eba8d-cb31-4d26-a759-b34f04bd6ff5 · outbound

This paper cites Scalable distributed DNN training using c ommodity GPU cloud com- puting,.

An End-to-End Encrypted Neural Network for Gradient Updates Transmission in Federated Learning Scalable distributed DNN training using c ommodity GPU cloud com- puting,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:45:05.721500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-14T11:45:05.474370Z digest=sha256:38aefd5bd898802248f9eb8b84e4b3561b43001c0c07cb8e4d2e6f02f29744e3

Observation 91c2a122-ba11-401f-8eb5-6833854b4450 · outbound

This paper cites Sparse Communication for Distributed Gradient Descent.

An End-to-End Encrypted Neural Network for Gradient Updates Transmission in Federated Learning Sparse Communication for Distributed Gradient Descent

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-14T11:45:05.479500Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T11:45:05.479500Z digest=sha256:74542f9906852876bdfecd48455a1703f714f08c92e0926a516be82d29c6194b

Observation 20fbd40e-e362-4a9e-9a6a-0e634c4f4b88 · outbound

This paper cites Federated Learning: Strategies for Improving Communication Efficiency.

An End-to-End Encrypted Neural Network for Gradient Updates Transmission in Federated Learning Federated Learning: Strategies for Improving Communication Efficiency

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-14T11:45:05.485235Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T11:45:05.485235Z digest=sha256:b51789e9cbd221edada0faef019c94abbd8864f9ddf131d357acb8367cfe1b29

Observation 09fc6b9f-1d19-4f7d-9664-e8b79376c45a · outbound

This paper cites Differentially Private Federated Learning: A Client Level Perspective.

An End-to-End Encrypted Neural Network for Gradient Updates Transmission in Federated Learning Differentially Private Federated Learning: A Client Level Perspective

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-14T11:45:05.490547Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T11:45:05.490547Z digest=sha256:048be869ad0407b9452dcc2fff40828a576165877cdfdd0cbb388e86ae9864e2

Observation 6f2d8bd2-2216-420a-8e1e-63d881d1987f · outbound

This paper cites Autoencoder for words,.

An End-to-End Encrypted Neural Network for Gradient Updates Transmission in Federated Learning Autoencoder for words,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:45:05.704309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-14T11:45:05.495897Z digest=sha256:b922c348f97d7006a78bde1d781692bd47b6fd953dfd653e65ca484ff5bf24f2

Observation e99b5b63-41ec-4acf-823b-8703e198a592 · outbound

This paper cites Using very deep a utoencoders for content- based image retrieval,.

An End-to-End Encrypted Neural Network for Gradient Updates Transmission in Federated Learning Using very deep a utoencoders for content- based image retrieval,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:45:05.688129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-14T11:45:05.500666Z digest=sha256:966167557781556e0d0a29fac6d5064c0be860682a16cf38e451c94b824f412b

Observation 54108d66-40dd-4762-a808-9acf2e7eaf2c · outbound

This paper cites Ex- tracting and composing robust features with denoising auto encoders,.

An End-to-End Encrypted Neural Network for Gradient Updates Transmission in Federated Learning Ex- tracting and composing robust features with denoising auto encoders,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:45:05.671314Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-14T11:45:05.505643Z digest=sha256:57541cc16076f2a2fd817ad876ca0eeff0a43eb53283bab077d80b71c51f3e45

Observation cda4c2de-fb85-46db-9bb1-919b65e57fa2 · outbound

This paper cites Fully homomorphic encryption using ide al lattices,.

An End-to-End Encrypted Neural Network for Gradient Updates Transmission in Federated Learning Fully homomorphic encryption using ide al lattices,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:45:05.653565Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-14T11:45:05.510163Z digest=sha256:d2d98f558554ec0eae0dd42d5cf2ccbd5336f7fbbbb01005498934b7ee51cf29

Observation d04248e1-6776-435b-88f7-f75dfb99b711 · outbound

This paper cites Deep Residual Learning for Image Recognition.

An End-to-End Encrypted Neural Network for Gradient Updates Transmission in Federated Learning Deep Residual Learning for Image Recognition

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-14T11:45:05.514888Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T11:45:05.514888Z digest=sha256:a7d0ef74ef6224e8446e715113b99d2ebcdccf662e5d476e0909d11a499f23fc

Pith citing papers

No inbound Pith citation observations are available.