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Paper Citation Record · LEDGER

Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning

As of 7 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2606.08252.

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

pith.paper-citation-record.v1
2606.08252 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-27T19:17:23.711817Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

39 of 39 outbound references displayed

  • verified exact7
  • verified fuzzy0
  • unresolved30
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1082e502-cce5-49ad-b3a4-6f909c453d58 · outbound

This paper cites an unresolved cited work.

Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning Unresolved cited work

Reference 1

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unresolved
no resolver link, observed 2026-06-27T19:17:23.711817Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation fbc414cf-db0b-482c-ae5f-d4d49302a57f · outbound

This paper cites Towards Understanding Ensemble, Knowledge Distillation and Self-Distillation in Deep Learning.

Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning Towards Understanding Ensemble, Knowledge Distillation and Self-Distillation in Deep Learning

Reference 2

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verified exact
arxiv_id, observed 2026-07-02T22:07:25.932947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 4bd57c72-9c92-478b-8a2d-6b2b772cd33f · outbound

This paper cites an unresolved cited work.

Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning Unresolved cited work

Reference 3

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source=pdf_text observed=2026-06-27T19:17:23.711817Z digest=sha256:4690eaa7f375c8f90f4ec6ec08638cf0852cc2ff537b193da6d689fc47e7e8ed

Observation e7745f14-b8da-4495-8338-64aa0465d081 · outbound

This paper cites an unresolved cited work.

Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning Unresolved cited work

Reference 4

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Observation 2dc5e6b1-1a60-439e-9b34-3e03da92c2ac · outbound

This paper cites an unresolved cited work.

Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning Unresolved cited work

Reference 5

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source=pdf_text observed=2026-06-27T19:17:23.711817Z digest=sha256:6e42ced30a871e2b1517e48dc4fb553645ef91779f54731107df2cae15143f74

Observation e9e18145-82e5-4531-9697-4600a2732db8 · outbound

This paper cites an unresolved cited work.

Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning Unresolved cited work

Reference 6

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-27T19:17:23.711817Z digest=sha256:946ff14a3181ab7dd9f129ebfbc849433fbc16b3502c2bb6c84f65a45e18995a

Observation d32b2646-5607-4e13-8935-31853244d67c · outbound

This paper cites an unresolved cited work.

Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning Unresolved cited work

Reference 7

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no resolver link, observed 2026-06-27T19:17:23.711817Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-27T19:17:23.711817Z digest=sha256:2eb802c7d6924e4043fb0a3a9b5808505da50322c2feb325ed16ce25e71df840

Observation 8a3011d7-6f2c-4276-9245-529c29aa93e1 · outbound

This paper cites an unresolved cited work.

Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning Unresolved cited work

Reference 8

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source=pdf_text observed=2026-06-27T19:17:23.711817Z digest=sha256:a5d50943f574573eb77076e9d744f8cb85144885431480b14e6d61c0ff7eef52

Observation 83459729-7e7e-4607-b72a-2f4b473713f7 · outbound

This paper cites an unresolved cited work.

Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning Unresolved cited work

Reference 9

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-27T19:17:23.711817Z digest=sha256:035a01a78e2ce1bea8f55f9d43ae0e97159348475cfea88df1f536f667856965

Observation de8c128e-d76a-4027-a7ef-9ee5ed5c09a5 · outbound

This paper cites an unresolved cited work.

Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning Unresolved cited work

Reference 10

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source=pdf_text observed=2026-06-27T19:17:23.711817Z digest=sha256:d96597ad6c812db3a7ae23ba5abe29db333033094df71db8999988ee295ab816

Observation 73dd3496-a549-47d4-a97d-28a8846aa1b8 · outbound

This paper cites an unresolved cited work.

Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning Unresolved cited work

Reference 11

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source=pdf_text observed=2026-06-27T19:17:23.711817Z digest=sha256:fa56dff9c5b276970a91dae68b534c340db920e96a1d1e1592a754c119ffc1df

Observation ee084170-4782-4c1d-bf42-8508425908b8 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning Distilling the Knowledge in a Neural Network

Reference 12

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verified exact
local_arxiv, observed 2026-07-02T22:07:25.938383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-27T19:17:23.711817Z digest=sha256:6ec41623fb6d44cfe202b53a7401932ba2cd20bce59a408a36f26729445f0c27

Observation 6af2d46d-5964-48a7-9452-913a38e5b509 · outbound

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

Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification

Reference 13

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local_arxiv, observed 2026-07-02T22:07:25.944042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-27T19:17:23.711817Z digest=sha256:2805b7f53159b021c6246e1a61e6e24e164995e6005369a45d86c638e423015c

Observation b96938fe-ee04-4ea2-9cc1-4826b09cd64b · outbound

This paper cites Communication-Efficient On-Device Machine Learning: Federated Distillation and Augmentation under Non-IID Private Data.

Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning Communication-Efficient On-Device Machine Learning: Federated Distillation and Augmentation under Non-IID Private Data

Reference 14

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verified exact
arxiv_id, observed 2026-07-02T22:07:25.940852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-27T19:17:23.711817Z digest=sha256:89c6896c172517140fa876004e4eac95888721e49d8a28fd69841f6c8c4ac1e0

Observation 0373f22c-2bd5-4a94-bf0c-67cc9439bd22 · outbound

This paper cites an unresolved cited work.

Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning Unresolved cited work

Reference 15

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Observation 71b2e125-9aaa-4513-94e0-a7bf2988ada6 · outbound

This paper cites Advances and Open Problems in Federated Learning.

Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning Advances and Open Problems in Federated Learning

Reference 16

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verified exact
arxiv_id, observed 2026-07-02T22:07:25.962385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-27T19:17:23.711817Z digest=sha256:5bff0dd7dc32d4adfe9b55edbca832a4835373c00186eee6b014588182f1dd30

Observation 5589ab00-95e6-4953-86a9-ea6987b83cf3 · outbound

This paper cites an unresolved cited work.

Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning Unresolved cited work

Reference 17

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Observation dab80392-ef77-4015-af3b-35b77064fa28 · outbound

This paper cites an unresolved cited work.

Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning Unresolved cited work

Reference 18

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source=pdf_text observed=2026-06-27T19:17:23.711817Z digest=sha256:c2f39a2dbad4efc8cc1989536743f8c67138c4c664122f160503bf77e4465b96

Observation 1fb2ba00-22e3-4892-9325-6789a11502c0 · outbound

This paper cites an unresolved cited work.

Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning Unresolved cited work

Reference 19

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source=pdf_text observed=2026-06-27T19:17:23.711817Z digest=sha256:9cddf69e010548dc138407f0badafae2da530ec41fd9aadd6dad0a9950b04912

Observation 15699118-8a7a-48c0-925b-4e8e217c8c63 · outbound

This paper cites an unresolved cited work.

Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning Unresolved cited work

Reference 20

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Observation 6ec19edc-b518-44c8-babe-f8108b95fb0b · outbound

This paper cites an unresolved cited work.

Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning Unresolved cited work

Reference 21

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Observation 134e1506-f5e7-4283-a16a-bbdbafc76f50 · outbound

This paper cites an unresolved cited work.

Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning Unresolved cited work

Reference 22

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source=pdf_text observed=2026-06-27T19:17:23.711817Z digest=sha256:6a5857cdc69ca3d47f8a3ed970a542a02fa24e0a1910fd93d7b8f180b76b8a10

Observation 9b5376a6-5ea8-480b-b820-cab435779b37 · outbound

This paper cites FedMD: Heterogenous Federated Learning via Model Distillation.

Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning FedMD: Heterogenous Federated Learning via Model Distillation

Reference 23

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arxiv_id, observed 2026-07-02T22:07:25.935692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-27T19:17:23.711817Z digest=sha256:858031199c67073e089f9afe27a50eabd094c25b21cf00c8d4d8ca7f484112de

Observation 05d0c48c-0db5-4ab1-ab4f-f9c6bd007c2a · outbound

This paper cites Practical One-Shot Federated Learning for Cross-Silo Setting.

Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning Practical One-Shot Federated Learning for Cross-Silo Setting

Reference 24

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arxiv_id, observed 2026-07-02T22:07:25.929817Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-27T19:17:23.711817Z digest=sha256:f35b5e58668ad3a52de642c02b828a18786c97599f543c346b19cc450f2b2067

Observation 31a04e11-2605-4de0-911b-2bf3e4ad8a8b · outbound

This paper cites an unresolved cited work.

Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning Unresolved cited work

Reference 25

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Observation bf05765e-61b5-4117-b1c2-65dc65f4387f · outbound

This paper cites an unresolved cited work.

Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning Unresolved cited work

Reference 26

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Observation 4a3271a8-a539-47b5-aed5-0b9b2fbbfe20 · outbound

This paper cites an unresolved cited work.

Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning Unresolved cited work

Reference 27

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Observation c530e983-85e3-459e-87a9-b180078c9755 · outbound

This paper cites an unresolved cited work.

Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning Unresolved cited work

Reference 28

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source=pdf_text observed=2026-06-27T19:17:23.711817Z digest=sha256:e8243536c8201a86f036db116af52f79556b18c9105f81a85fd856485fac4287

Observation 0dc2bb3d-0623-41b1-b0aa-be90062a2f51 · outbound

This paper cites an unresolved cited work.

Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning Unresolved cited work

Reference 29

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Observation 3b7ef116-181c-4eeb-a988-8dbf7a073ab6 · outbound

This paper cites an unresolved cited work.

Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning Unresolved cited work

Reference 30

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source=pdf_text observed=2026-06-27T19:17:23.711817Z digest=sha256:c1fcb4ce64c789ac33d14c28dd8ab537bc0df21598ed4ff9d5d55f9e817551f3

Observation dc9b8a58-b84f-41ae-a831-09bbc1871ba3 · outbound

This paper cites an unresolved cited work.

Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning Unresolved cited work

Reference 31

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Observation bae9bd1b-3ddf-4c15-97f9-50c612396db4 · outbound

This paper cites an unresolved cited work.

Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning Unresolved cited work

Reference 32

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source=pdf_text observed=2026-06-27T19:17:23.711817Z digest=sha256:1a2d313d78ac1801c2324850cff7cdb37144d9a079a10a8e8874a9b33768f95e

Observation a7b9f5f8-93eb-4f52-ac60-eb9ac3be6f53 · outbound

This paper cites an unresolved cited work.

Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning Unresolved cited work

Reference 33

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source=pdf_text observed=2026-06-27T19:17:23.711817Z digest=sha256:7b6c490c05257dae3dc8522abb9b879930b2327b837ae2fd53dbe61116cfa9db

Observation da6afb34-9ea3-42d3-8220-95c97ebabdfc · outbound

This paper cites an unresolved cited work.

Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning Unresolved cited work

Reference 34

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Observation 2f987958-0f4c-4623-9a1a-0ce7888a0d2f · outbound

This paper cites author Stronati, M.

Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning author Stronati, M

Reference 35

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doi, observed 2026-06-27T19:21:10.621245Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-27T19:17:23.711817Z digest=sha256:06a2af1043271d32c6aea0c28c00f50177c2b67c77cfe6637325d340f7892ff3

Observation 2443808f-47fa-4772-8604-4f0d856fe75b · outbound

This paper cites an unresolved cited work.

Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning Unresolved cited work

Reference 36

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Observation 4b72c3cf-f992-44f8-8258-b7678002223c · outbound

This paper cites an unresolved cited work.

Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning Unresolved cited work

Reference 37

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Observation e15fdee0-1569-4686-b757-ffe1b4499e86 · outbound

This paper cites an unresolved cited work.

Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning Unresolved cited work

Reference 38

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source=pdf_text observed=2026-06-27T19:17:23.711817Z digest=sha256:53765cea71f69d69ba1e86ee5ccad9413ab6a2b79804c11aeded69f2831f709a

Observation db7ecc81-d1d2-4107-9492-4ed967dcef23 · outbound

This paper cites an unresolved cited work.

Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning Unresolved cited work

Reference 39

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source=pdf_text observed=2026-06-27T19:17:23.711817Z digest=sha256:0ce4a5b8aa5af05c521b7fb29dee6ba38f7a98d2db546fb9a64f79da0ff5da4b

Pith citing papers

No inbound Pith citation observations are available.