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Paper Citation Record · LEDGER

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

As of 16 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 2026-08-16T06:30:59.297886+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:df0cf3f41f6e70197c5681d7e4de7ebfec51c2fc98691ab60fc47d748a978736

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T11:45:05.458556Z digest=sha256:74567d7cb3a37ff84d9b4a8cd5fd97e469d0a211f1daa366f00dc3d46cfa5ba3

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T11:45:05.463716Z digest=sha256:c2b480dce5e2eb83e02fa9fda2f5f3be2ff9da6983f8ea16b3d8f28af99e1c34

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T11:45:05.474370Z digest=sha256:915d9468ac894e7607ae91c2970ab97b4b81e8cfc1a7924f60331fae642825b6

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T11:45:05.495897Z digest=sha256:fb79d5baf5b2edac7e26176d8ef35b502b9816396e7804f886be0ec4cd3bf199

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T11:45:05.500666Z digest=sha256:daa0413ca1ac622d79afb003cbd93d5868e9121e9c0eb68b25dd3ad6271451c9

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T11:45:05.505643Z digest=sha256:03d9e54c0fc5001b20fd8cf16806c34471b8e0fdb351caa21e25e9dfa1361043

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T11:45:05.510163Z digest=sha256:6dac96f1ee8a5886029d9003f3559531a861260593739b82c58b38dadceb64f0

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.