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Paper Citation Record · LEDGER

Tackling Data Heterogeneity in Federated Learning through Knowledge Distillation with Inequitable Aggregation

As of 9 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2506.20431.

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

pith.paper-citation-record.v1
2506.20431 v1

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:52:41.339781Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

36 of 36 outbound references displayed

  • verified exact3
  • verified fuzzy8
  • unresolved25
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c0101aac-e2f1-4e4a-94bb-0beb61c613cc · outbound

This paper cites Zhang, Y.

Tackling Data Heterogeneity in Federated Learning through Knowledge Distillation with Inequitable Aggregation Zhang, Y

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:52:45.771854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:52:38.288766Z digest=sha256:94c64841e72b260129a22417793576f8bdaad6a5637c84f2985cb1b3876801f3

Observation eb171267-c8ae-4316-8593-b26425c29203 · outbound

This paper cites McMahan, E.

Tackling Data Heterogeneity in Federated Learning through Knowledge Distillation with Inequitable Aggregation McMahan, E

Reference 2

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verified fuzzy
raw_fallback, observed 2026-08-06T22:52:45.677518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:52:38.388655Z digest=sha256:784ce8283d828dc0cc831024f90709b4aabc2fb0f1c7cc4cac1ad040e037bba8

Observation f51c6e70-37d3-49f2-9e94-ad6771193f06 · outbound

This paper cites an unresolved cited work.

Tackling Data Heterogeneity in Federated Learning through Knowledge Distillation with Inequitable Aggregation Unresolved cited work

Reference 3

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:52:45.543774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:52:38.457974Z digest=sha256:1b12fea6413f17179b22b17806923a9f222be5d55bdf837922622573d36dee2b

Observation ad4bd3f7-1833-4eaf-b22d-9b380c67dd34 · outbound

This paper cites Federated Learning with Non-IID Data.

Tackling Data Heterogeneity in Federated Learning through Knowledge Distillation with Inequitable Aggregation Federated Learning with Non-IID Data

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-06T22:52:38.545634Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:52:38.545634Z digest=sha256:0522a731cced2a83aa05a1fb8ba2deb68b7473f1c4a6bf810a921b2f547d4c95

Observation f64723be-e1f2-47a7-b1b5-7b32e3a8523f · outbound

This paper cites an unresolved cited work.

Tackling Data Heterogeneity in Federated Learning through Knowledge Distillation with Inequitable Aggregation Unresolved cited work

Reference 5

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:52:45.437070Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:52:38.595908Z digest=sha256:e0a893166a8c53620eac84cb640a577b628db06d62b84ec29a34aafbb124ae0b

Observation 239c833e-c171-4045-bffb-329eeea85e0f · outbound

This paper cites an unresolved cited work.

Tackling Data Heterogeneity in Federated Learning through Knowledge Distillation with Inequitable Aggregation Unresolved cited work

Reference 6

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:52:45.311995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:52:38.703738Z digest=sha256:80595c94793043f87ce81b2b2c1224848987c22cf3506bb36eeba1847f3c053c

Observation 26bfc576-3f74-4710-a4c9-190897cac99e · outbound

This paper cites an unresolved cited work.

Tackling Data Heterogeneity in Federated Learning through Knowledge Distillation with Inequitable Aggregation Unresolved cited work

Reference 7

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:52:45.162982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:52:38.809017Z digest=sha256:329f8366e7398ca3f4506a043e0ee633587976ae0a1f54d757800c9b263e784e

Observation 637ae18f-d846-4857-8424-d7977b25e607 · outbound

This paper cites an unresolved cited work.

Tackling Data Heterogeneity in Federated Learning through Knowledge Distillation with Inequitable Aggregation Unresolved cited work

Reference 8

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:52:45.020908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:52:38.896754Z digest=sha256:d0c070e0dec3879853e5023a445c2cbd3499c3cd3bbf53033ad5a26f6eb4a3a2

Observation 8361aaa7-a8bb-4a60-8fbd-03fb2f5627be · outbound

This paper cites an unresolved cited work.

Tackling Data Heterogeneity in Federated Learning through Knowledge Distillation with Inequitable Aggregation Unresolved cited work

Reference 9

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:52:44.865487Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:52:38.986874Z digest=sha256:bdf16448de733a854573dd50fcdc3d1faec7b4bb6fa9e6f5522c176fedc3bf5a

Observation bdcd4d4e-1f8b-4394-aa86-ddbedd9a5db9 · outbound

This paper cites Communication-Efficient Federated Learning via Optimal Client Sampling.

Tackling Data Heterogeneity in Federated Learning through Knowledge Distillation with Inequitable Aggregation Communication-Efficient Federated Learning via Optimal Client Sampling

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-06T22:52:39.072124Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:52:39.072124Z digest=sha256:b8f708848b7b7df16ed1e2c5c52e21b6e5d936bb2f16ead4e3c5727e0a9e8a81

Observation 5c1813ee-d2a1-4668-9334-ced156400c89 · outbound

This paper cites an unresolved cited work.

Tackling Data Heterogeneity in Federated Learning through Knowledge Distillation with Inequitable Aggregation Unresolved cited work

Reference 11

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:52:44.696761Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:52:39.161317Z digest=sha256:995cce658e573647c2428367f15569d3df208e5eeddc071e7897a6b409492916

Observation e9cfcfbc-838c-4b1c-ac06-9ebba7acd01f · outbound

This paper cites an unresolved cited work.

Tackling Data Heterogeneity in Federated Learning through Knowledge Distillation with Inequitable Aggregation Unresolved cited work

Reference 12

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:52:44.542736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:52:39.232479Z digest=sha256:b123ea05292118f1e1421263953155041a322393c549d73b4e18a2dbbb202784

Observation 920b8a47-f759-4228-955f-c12a691ed957 · outbound

This paper cites an unresolved cited work.

Tackling Data Heterogeneity in Federated Learning through Knowledge Distillation with Inequitable Aggregation Unresolved cited work

Reference 13

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:52:44.391348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:52:39.287727Z digest=sha256:bbefa9fdb40db9237abfcc194c04e51e287d7f93c68dbb3c1c8f4c764382e896

Observation 51478fb1-75af-45c2-901e-a2d753964dbb · outbound

This paper cites Li, D.-C.

Tackling Data Heterogeneity in Federated Learning through Knowledge Distillation with Inequitable Aggregation Li, D.-C

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:52:44.208143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:52:39.374413Z digest=sha256:1ee0229c414dbb5a5e1a5d4cb4b4f038387dfcb996c64e1ca1546b6e5f9aa5bf

Observation f181d46d-3eed-4e33-a4d7-59be6d6ff047 · outbound

This paper cites Zhang, Y.

Tackling Data Heterogeneity in Federated Learning through Knowledge Distillation with Inequitable Aggregation Zhang, Y

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:52:44.025992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:52:39.481762Z digest=sha256:be9ee7525dc5a8f0e2f1ece2b43e2d331aa1ac9ddb7d669b2725de46574cfc48

Observation 6025fece-e425-46e1-adf5-9bbb1cfe3e79 · outbound

This paper cites an unresolved cited work.

Tackling Data Heterogeneity in Federated Learning through Knowledge Distillation with Inequitable Aggregation Unresolved cited work

Reference 16

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:52:43.863322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:52:39.550785Z digest=sha256:e5c782bda6e991ded83a3ad53fbb02ea39e7e4adf267d0faa0fc44bf23359287

Observation 2594e441-1f16-4fd2-9aef-089769c469bc · outbound

This paper cites Towards Understanding and Mitigating Dimensional Collapse in Heterogeneous Federated Learning.

Tackling Data Heterogeneity in Federated Learning through Knowledge Distillation with Inequitable Aggregation Towards Understanding and Mitigating Dimensional Collapse in Heterogeneous Federated Learning

Reference 17

Resolution
verified exact
local_arxiv, observed 2026-08-06T22:52:42.135684Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:52:39.623313Z digest=sha256:27f8c5d6d2c012cd4c87e54ccea37e5f647c6519fa20f0f3fbfe8f690040bc6b

Observation 170016cc-8097-416f-ac3f-f8b99e8992b6 · outbound

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

Tackling Data Heterogeneity in Federated Learning through Knowledge Distillation with Inequitable Aggregation Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-06T22:52:39.717052Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:52:39.717052Z digest=sha256:1688596b8c184b016bde7899ffc86008a2d10fe51a5515cac5a8b4b0a8057135

Observation 6f5a7a5d-88fd-4571-a8d6-9de01fb95310 · outbound

This paper cites Zhang, L.

Tackling Data Heterogeneity in Federated Learning through Knowledge Distillation with Inequitable Aggregation Zhang, L

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:52:43.683342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:52:39.807500Z digest=sha256:be1f635b0e94a3a1b0ef134c85f370d696ac08ef48495c36ac6acd6538cf885c

Observation ad2ddecf-d824-41f1-932f-072c1b03f3cf · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Tackling Data Heterogeneity in Federated Learning through Knowledge Distillation with Inequitable Aggregation Distilling the Knowledge in a Neural Network

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-06T22:52:39.910801Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:52:39.910801Z digest=sha256:c743f7542a39f2f3a48c37cc3ebe24eafce1f6607122f373c16c5dea27dd10f0

Observation 7e893ef4-28a1-4604-a746-359a4315b5fb · outbound

This paper cites Knowledge Distillation in Federated Learning: a Survey on Long Lasting Challenges and New Solutions.

Tackling Data Heterogeneity in Federated Learning through Knowledge Distillation with Inequitable Aggregation Knowledge Distillation in Federated Learning: a Survey on Long Lasting Challenges and New Solutions

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-06T22:52:39.994072Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:52:39.994072Z digest=sha256:0da9f2b65ded7ed3baa5ad6509b5479bdbc0b73b59b2f1d5678ac78bae7554cf

Observation 10fb3272-81c2-4fa8-a074-d468faef0093 · outbound

This paper cites an unresolved cited work.

Tackling Data Heterogeneity in Federated Learning through Knowledge Distillation with Inequitable Aggregation Unresolved cited work

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-06T22:52:40.079451Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:52:40.079451Z digest=sha256:bc6e1cf7d17e7f19501e7abb94c3bd2a43af0cfa18be35b83eed2692d3eaa3c0

Observation d3fe519b-08b5-401e-ac27-8fcbd8ab411e · outbound

This paper cites Federated Knowledge Distillation.

Tackling Data Heterogeneity in Federated Learning through Knowledge Distillation with Inequitable Aggregation Federated Knowledge Distillation

Reference 23

Resolution
verified exact
local_arxiv, observed 2026-08-06T22:52:41.898944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:52:40.184500Z digest=sha256:359f5cb24b353e2efac51a25a83db027901898419415c0ab9e0adc35ac39d2a4

Observation cf4ae9cb-b856-41f3-81fe-fb3d53cd0abc · outbound

This paper cites Local-Global Knowledge Distillation in Heterogeneous Federated Learning with Non-IID Data.

Tackling Data Heterogeneity in Federated Learning through Knowledge Distillation with Inequitable Aggregation Local-Global Knowledge Distillation in Heterogeneous Federated Learning with Non-IID Data

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-06T22:52:40.261436Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:52:40.261436Z digest=sha256:bea94aa52217e72156bd1c05728366e946b4f2a7f8450b3e908b63b9586e3a7d

Observation c219fc7d-10a8-4e98-ba8a-2646d10aee94 · outbound

This paper cites Xiong, R.

Tackling Data Heterogeneity in Federated Learning through Knowledge Distillation with Inequitable Aggregation Xiong, R

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:52:43.513571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:52:40.335664Z digest=sha256:59fdccfa9c42a162b17775fea6701233e1619b95723c4be7f4d800395ece0247

Observation 3c1c2617-e8c3-4610-97c3-084cd8832ab2 · outbound

This paper cites an unresolved cited work.

Tackling Data Heterogeneity in Federated Learning through Knowledge Distillation with Inequitable Aggregation Unresolved cited work

Reference 26

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:52:43.356501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:52:40.422766Z digest=sha256:602c42fc25f351c67b7cb048defcc16b2c24042949ab5f145b00c81d649eecb2

Observation 6c2c64dd-4ea0-44cb-863c-fa648ca8af31 · outbound

This paper cites Handling Data Heterogeneity in Federated Learning via Knowledge Distillation and Fusion.

Tackling Data Heterogeneity in Federated Learning through Knowledge Distillation with Inequitable Aggregation Handling Data Heterogeneity in Federated Learning via Knowledge Distillation and Fusion

Reference 27

Resolution
verified exact
local_arxiv, observed 2026-08-06T22:52:41.661039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:52:40.500611Z digest=sha256:0fd6e607762456c94e048a3c4ba219cef1b8bfd0bf0bb139608bff09a334602e

Observation 0172acb0-8e09-4f5f-98af-940115e6e94f · outbound

This paper cites Conditional Generative Adversarial Nets.

Tackling Data Heterogeneity in Federated Learning through Knowledge Distillation with Inequitable Aggregation Conditional Generative Adversarial Nets

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-06T22:52:40.593487Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:52:40.593487Z digest=sha256:772a4b1b117ef02e2ba07d4103454efa99b04c1c9e3128ec35dc4b089b7e6baa

Observation b3604f1e-245b-4e73-b9ff-5ffeec53e961 · outbound

This paper cites FedCG: Leverage Conditional GAN for Protecting Privacy and Maintaining Competitive Performance in Federated Learning.

Tackling Data Heterogeneity in Federated Learning through Knowledge Distillation with Inequitable Aggregation FedCG: Leverage Conditional GAN for Protecting Privacy and Maintaining Competitive Performance in Federated Learning

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-06T22:52:40.666203Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:52:40.666203Z digest=sha256:53875aa1caab8508d6cc9056064ad8b9e47db74fcaebe1e1293f5a778c00928c

Observation 56eae987-524c-465c-8033-64537a4794d6 · outbound

This paper cites Furlanello, Z.

Tackling Data Heterogeneity in Federated Learning through Knowledge Distillation with Inequitable Aggregation Furlanello, Z

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:52:43.196619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:52:40.804607Z digest=sha256:85be5ac7261e873ce229548c04e6f26d43dc480552d5b5b83acc07da663387a8

Observation d12e9a7e-90af-4df5-a3fa-722f2734bdd0 · outbound

This paper cites an unresolved cited work.

Tackling Data Heterogeneity in Federated Learning through Knowledge Distillation with Inequitable Aggregation Unresolved cited work

Reference 31

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:52:42.961871Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:52:40.883565Z digest=sha256:146c8482c08e66147daa5b15af5619f6779a5a72add9e99990875a01d23abb11

Observation 12b845ac-e7c7-4deb-be60-bf7baa9e82a2 · outbound

This paper cites Revisiting Knowledge Distillation via Label Smoothing Regularization.

Tackling Data Heterogeneity in Federated Learning through Knowledge Distillation with Inequitable Aggregation Revisiting Knowledge Distillation via Label Smoothing Regularization

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-06T22:52:40.960442Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:52:40.960442Z digest=sha256:735dff40025e0cfb766b26ce5fb636e758dcb8f9ab319a1087b8fd5363a7a4d4

Observation 3c5fd6cd-f100-44fe-b0dd-9b49749c93cb · outbound

This paper cites Federated Learning with Matched Averaging.

Tackling Data Heterogeneity in Federated Learning through Knowledge Distillation with Inequitable Aggregation Federated Learning with Matched Averaging

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-06T22:52:41.048505Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:52:41.048505Z digest=sha256:b05419590c6245d948ae8e218647dc7129dad7882724140ed52c6218195ffa16

Observation 9cdc981d-8767-4786-a69a-9f6572f88739 · outbound

This paper cites Self-Knowledge Distillation with Progressive Refinement of Targets.

Tackling Data Heterogeneity in Federated Learning through Knowledge Distillation with Inequitable Aggregation Self-Knowledge Distillation with Progressive Refinement of Targets

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-06T22:52:41.154912Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:52:41.154912Z digest=sha256:6b496ea97aca91ac9bd2faf4a8cfa19893d6a2088a51f293641e2fbb8c56095b

Observation 323d86f9-0c29-4f30-8426-0ef94f507ef4 · outbound

This paper cites an unresolved cited work.

Tackling Data Heterogeneity in Federated Learning through Knowledge Distillation with Inequitable Aggregation Unresolved cited work

Reference 35

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:52:42.655374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:52:41.261451Z digest=sha256:bfbc3688aa1151c1ddd848f5837076ebd39daa64bbd0265605271eed54607abb

Observation eb5aa57b-36c2-4b12-99dc-ade51fbed962 · outbound

This paper cites Kairouz, H.

Tackling Data Heterogeneity in Federated Learning through Knowledge Distillation with Inequitable Aggregation Kairouz, H

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:52:42.397423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T22:52:41.339781Z digest=sha256:6f3bdd986c6c7d922ffebb5b50046c76a2eeff3a4a39cfab14abe6a1d8376933

Pith citing papers

No inbound Pith citation observations are available.