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Paper Citation Record · LEDGER

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

As of 8 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 2026-08-07T06:34:17.273281+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

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:52:38.288766Z digest=sha256:d2c8ed2044f5d21892e6bea506391bcd7c41876c320e020f62695e3b19670dfb

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:52:38.388655Z digest=sha256:17ae939b6123e9c09411e06baa85eb7f67f3cb860103ad6dec9d1f3895af4076

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:52:38.457974Z digest=sha256:233d502488d472364da0ae562e5b0ae32414d96c1f0c0b47a52dae0893c01600

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=sha256:1c7d6498550c058aa890c6fef9148415b849e11b02c11f3d8b5ebd6baba5017d

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:52:38.595908Z digest=sha256:85a1eb9b469803e1eece629c22ca2735c988bb42ed079f9f3c1688e09dc68739

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:52:38.703738Z digest=sha256:6b4d361db27ed22f17fec078882784c935dcddfedcac5f8afd695f56cbd94635

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:52:38.809017Z digest=sha256:7ac06c04b011bd3d9d691f2695aa68db257d12081cae2f16389659580bc94271

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:52:38.896754Z digest=sha256:779bef941da9cb76b5a25f85979522682c98cb18b55e047c5d4ce2a1bed51464

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:52:38.986874Z digest=sha256:f366732b066af1e0b642869fdfb4ad76e064f7817f158e9671022622ebc9a51f

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=sha256:94f77905f64be2747e7965536c8729631e79dadbd9c8ff514be9e14f713cdade

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:52:39.161317Z digest=sha256:74ae8d39304f63de1bd44e7d8a21ede9de97dbcee8132fc8954cd0196ca0ed74

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:52:39.232479Z digest=sha256:78e7e1ff17bd765704352e610e643c8a0d7c12b271ee79618d61b5f1d335aee9

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:52:39.287727Z digest=sha256:15252976eeab43d02b9b6bc8cdcb5d340693002e5647a0ea736b42fedaec26b6

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:52:39.374413Z digest=sha256:055c3077b63ea4bd2014f615bc30bb1552edd0d8a92aa648b00ec4d6efdf281c

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:52:39.481762Z digest=sha256:7a936b4541a8a6b422e42cd3c8e13ce41138fdce4481a24462f0c53fbd2dd811

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:52:39.550785Z digest=sha256:780a1b9689f9058c6f03e5f340b06425aa52c823cb02cf246789975fbb358a86

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:52:39.623313Z digest=sha256:8c0058cece150814ab0eaf3e28b70e4ede7d01e5f761e89b64ddd2004c147c9c

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=sha256:0ef37e2e3dc4d7674c0a252da343cbd46d9756debd59dfd1f2760bcc7b2e08ae

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:52:39.807500Z digest=sha256:3372bc8606109f9df37868785ea709025e971716c5a2400430d5a377efe0833c

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

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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=sha256:46b0eb12a525e31c015ad6e1e100882ae88dc5fdb978491ee507b097a203cb4f

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:c6a3cf1f43ed93244bdf6529abe8cb6631b21e188742da244985fce27ea5eeba

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=sha256:0bc773063394a6dc9fb25330f240b347966af845bcc4e714a53bcf3f9d2c36da

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:52:40.184500Z digest=sha256:e1d3c34d3097220250ef8d34cc2a55776546025b7ca3b31b45f959820ce120b2

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:efbee099a2a5f7ebf6dc15d1c6b494a0f9cb0f9592724224146de5a5be2c5715

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:52:40.335664Z digest=sha256:a2fe6ed5b5f520afb31e4e68969059bcd2157868577653449ae5644d1aee31d6

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:52:40.422766Z digest=sha256:db46c12712583ad15b0375a81366ba2ba1930cca7dadc08ca27bf997ad8f2d5a

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:52:40.500611Z digest=sha256:5d76c195aa7d00b22e5ee7fb79bd40ce1ca2b2ceecbfaaef1f10fc16b9bd7d05

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:daf1b202e178cbc1c86d72ea5a58e902e79fe590334d103d260842a34c1269f8

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=sha256:62471c5d7c603973b1e25c58de1da82afb34ac9cae97e7554e84d85251a37a50

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:52:40.804607Z digest=sha256:4eaaef657ccc176d95da3f9d1984395f320842ae044e268c496e60d088848e32

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:52:40.883565Z digest=sha256:c4b6c8a139a0c5f9ddd50a89ea7775752fb23dbeb1cd3357d82b066a8014226b

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=sha256:5b29b1bc19b81a520a122e83d1161160e5d3261cb8a977c378a89246ff2d9558

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=sha256:34a461c112c14cffc679a9c50986cb3b3e1403cfdb21197c681c36d2f38ed291

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=sha256:3136ffe9cb84eb5b7f1fec8d5bcf211721e529d47093697021e756a97a1f5560

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:52:41.261451Z digest=sha256:85844f3f7123bf2f09c3d4878d2bc9b2e90aa8dfec8ee14d6f9d5f834d99bfab

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:52:41.339781Z digest=sha256:f04e9c9c591025d1dee39c36d20add005bbb512276bd6ef84b7baee160a6921d

Pith citing papers

No inbound Pith citation observations are available.