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Paper Citation Record · LEDGER

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity

As of 17 August 2026, this Paper Citation Record lists 70 of 70 outbound references and 0 inbound Pith citation observations for arXiv:2506.00932.

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

pith.paper-citation-record.v1
2506.00932 v1

Coverage vector

measured 70 of 70 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:01:30.460023Z

measured 70 of 70 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

70 of 70 outbound references displayed

  • verified exact0
  • verified fuzzy49
  • unresolved21
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bd18ff49-d22e-42cc-90f5-eb9b14fc5a89 · outbound

This paper cites Federated Residual Learning.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Federated Residual Learning

Reference 1

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-07T12:01:26.489970Z digest=sha256:82b0b9d885226934ff5f48d39b011a965e2db2bdb3d521407f345fe1c625ff82

Observation 8ce2b3d6-0075-48ac-8fb7-c66b83d8ab85 · outbound

This paper cites Federated Learning with Personalization Layers.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Federated Learning with Personalization Layers

Reference 2

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no resolver link, observed 2026-08-07T12:01:26.578832Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 93ad584f-1338-4208-ae4e-4228212a36b6 · outbound

This paper cites Revisiting sparsity hunting in federated learning: Why does sparsity consensus matter? Transactions on Machine Learning Research, 2023.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Revisiting sparsity hunting in federated learning: Why does sparsity consensus matter? Transactions on Machine Learning Research, 2023

Reference 3

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verified fuzzy
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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.

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Observation 3c7cc53a-4987-4350-98e6-28e5a1b960bb · outbound

This paper cites Federated dynamic sparse training: Computing less, communicating less, yet learning better.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Federated dynamic sparse training: Computing less, communicating less, yet learning better

Reference 4

Resolution
verified fuzzy
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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=arxiv_source observed=2026-08-07T12:01:26.723592Z digest=sha256:ad889bfbe7da3dd4c380999cfad053f7e3f5a07ec5090d802ce5c7c9fd47f0ac

Observation 60f95234-a79e-459d-996c-a93946f0459f · outbound

This paper cites Efficient personalized federated learning via sparse model-adaptation.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Efficient personalized federated learning via sparse model-adaptation

Reference 5

Resolution
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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=arxiv_source observed=2026-08-07T12:01:26.815025Z digest=sha256:0f57fd46dc365846ad594e72693ef5d283fa0226a319cf29acf834e9fd9d1337

Observation 669fe05f-b242-43be-8688-c1cadb19eda4 · outbound

This paper cites Sparsity winning twice: Better robust generalization from more efficient training.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Sparsity winning twice: Better robust generalization from more efficient training

Reference 6

Resolution
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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.

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Observation bf98c37c-7db3-4bc7-a170-8b1eae76eedc · outbound

This paper cites Streamlining redundant layers to compress large language models.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Streamlining redundant layers to compress large language models

Reference 7

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verified fuzzy
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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=arxiv_source observed=2026-08-07T12:01:26.949521Z digest=sha256:202a7b6f9ef981b2c800bc223064cc486cdf817169542cdd106c683060faa405

Observation a399483b-deb4-4fdd-94af-6a4a89acc261 · outbound

This paper cites Exploiting shared representations for personalized federated learning.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Exploiting shared representations for personalized federated learning

Reference 8

Resolution
verified fuzzy
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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=arxiv_source observed=2026-08-07T12:01:27.005979Z digest=sha256:9ee6b5c92c1ba380c5aa1c20e5d6d92065c8f22a32550e3d094b0635a67a8652

Observation cfd3b0d8-01f1-4add-b9c4-f606d2b9705e · outbound

This paper cites Dispfl: Towards communication-efficient personalized federated learning via decentralized sparse training.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Dispfl: Towards communication-efficient personalized federated learning via decentralized sparse training

Reference 9

Resolution
verified fuzzy
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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=arxiv_source observed=2026-08-07T12:01:27.073863Z digest=sha256:6cd172ed466c43bdbd454c2ba29aff20409721ef752038c2e34bbe1491ff0732

Observation 20d57a25-549a-45b3-a006-ade206a6c240 · outbound

This paper cites Flexible clustered federated learning for client-level data distribution shift.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Flexible clustered federated learning for client-level data distribution shift

Reference 10

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raw_fallback, observed 2026-08-07T12:01:37.686790Z

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=arxiv_source observed=2026-08-07T12:01:27.162666Z digest=sha256:5be4d4435f115fbfa33d13b02d0379527cf2a154671ab0f4b8e2d7a80472ba17

Observation bf036771-f99e-480e-a401-0cc50eafe61d · outbound

This paper cites Rigging the lottery: Making all tickets winners.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Rigging the lottery: Making all tickets winners

Reference 11

Resolution
verified fuzzy
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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=arxiv_source observed=2026-08-07T12:01:27.215567Z digest=sha256:cc77d806563c768475dcc830c0360c0fa1045532015bae6ec1fd23159a1fb0e8

Observation ba925d77-4cd8-41c0-acb1-327624e235b9 · outbound

This paper cites Gradient flow in sparse neural networks and how lottery tickets win.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Gradient flow in sparse neural networks and how lottery tickets win

Reference 12

Resolution
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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.

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Observation d6f27798-5cb3-4a44-8e82-eb279c64a643 · outbound

This paper cites An efficient framework for clustered federated learning.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity An efficient framework for clustered federated learning

Reference 13

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:01:27.291459Z digest=sha256:de4c203440c8a86154528cc0917b28eefde8b3655bba426d57d599a39d49f03c

Observation 0973ca7e-86a6-4117-bf62-179706e0dbe4 · outbound

This paper cites The unreasonable ineffectiveness of the deeper layers.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity The unreasonable ineffectiveness of the deeper layers

Reference 14

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verified fuzzy
raw_fallback, observed 2026-08-07T12:01:37.157277Z

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=arxiv_source observed=2026-08-07T12:01:27.357514Z digest=sha256:b612cfe8db32c4b97cc933a64e44558033425b9baf11dcfab98094bdf24f4fd8

Observation 27e8c6be-aaef-4ed7-9e5d-d9b279c52d4c · outbound

This paper cites Adaptive gradient sparsification for efficient federated learning: An online learning approach.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Adaptive gradient sparsification for efficient federated learning: An online learning approach

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:01:36.988387Z

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=arxiv_source observed=2026-08-07T12:01:27.423364Z digest=sha256:da4290856772c22d6d33957476f174e835e7be7956bdd263c107f1786c87446a

Observation 106717aa-ad8b-410e-bd85-3f54af56448e · outbound

This paper cites Deep residual learning for image recognition.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Deep residual learning for image recognition

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-07T12:01:27.475372Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:01:27.475372Z digest=sha256:5fc1b0ab38c625b09f8994a7558dcb39af9849ac943c34137d0abaf8523b9467

Observation c4c8c3de-894b-4db0-a10f-98f5a091e611 · outbound

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

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T12:01:27.520931Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 6509ea1d-d41d-4471-b2c6-44dd5ec7594c · outbound

This paper cites Achieving Personalized Federated Learning with Sparse Local Models.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Achieving Personalized Federated Learning with Sparse Local Models

Reference 18

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no resolver link, observed 2026-08-07T12:01:27.581157Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation edf3af38-5e02-452b-bf40-96ec5c151f67 · outbound

This paper cites Federated learning via meta-variational dropout.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Federated learning via meta-variational dropout

Reference 19

Resolution
verified fuzzy
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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.

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Observation bd7b1744-7e11-4eae-aaf9-42b54c07da37 · outbound

This paper cites Tracing representation progression: Analyzing and enhancing layer-wise similarity.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Tracing representation progression: Analyzing and enhancing layer-wise similarity

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:01:36.658048Z

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.

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Observation 3d78df12-90df-480a-b9d3-063cfe818825 · outbound

This paper cites Complement sparsification: Low-overhead model pruning for federated learning.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Complement sparsification: Low-overhead model pruning for federated learning

Reference 21

Resolution
verified fuzzy
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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.

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Observation 533696a9-288b-49e3-bc85-c6696eefa77c · outbound

This paper cites Improving Federated Learning Personalization via Model Agnostic Meta Learning.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Improving Federated Learning Personalization via Model Agnostic Meta Learning

Reference 22

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no resolver link, observed 2026-08-07T12:01:27.817834Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:01:27.817834Z digest=sha256:1f438c36a97b9ec2031370600799bc842f50995d67b4dadcc4f0595e77dcb105

Observation 5843090a-560f-404d-90df-ee5d51913cb0 · outbound

This paper cites Model pruning enables efficient federated learning on edge devices.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Model pruning enables efficient federated learning on edge devices

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:01:36.322643Z

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.

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Observation c255d1fb-69cf-489a-bb4d-7dcbd3bcb8d9 · outbound

This paper cites Personalized edge intelligence via federated self-knowledge distillation.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Personalized edge intelligence via federated self-knowledge distillation

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:01:36.166447Z

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.

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Observation 3ae056c8-087e-463c-98b6-0e326b819a15 · outbound

This paper cites Scaffold: Stochastic controlled averaging for federated learning.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Scaffold: Stochastic controlled averaging for federated learning

Reference 25

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no resolver link, observed 2026-08-07T12:01:27.959097Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 584ae726-696f-4d13-914d-d9aff6145fa9 · outbound

This paper cites Learning multiple layers of features from tiny images.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Learning multiple layers of features from tiny images

Reference 26

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unresolved
no resolver link, observed 2026-08-07T12:01:28.003320Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:01:28.003320Z digest=sha256:aa2db0a4d5cac9c62632cc536e220e433bc09e9865cb04a40606827b81e61f8b

Observation 8b0ab7a4-1464-4c60-ab24-c5a2cbe751c4 · outbound

This paper cites Cifar-10 (canadian institute for advanced research).

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Cifar-10 (canadian institute for advanced research)

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:01:35.994018Z

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=arxiv_source observed=2026-08-07T12:01:28.041244Z digest=sha256:a9a93210bc3ea38d7be19b56c4b9c7124dfe4493de223108d1273f5248b13aeb

Observation 4a1b130f-7aeb-4656-8240-86299938dd06 · outbound

This paper cites Federated LoRA with Sparse Communication.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Federated LoRA with Sparse Communication

Reference 28

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unresolved
no resolver link, observed 2026-08-07T12:01:28.092790Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:01:28.092790Z digest=sha256:ce7939c4a49ec2a3b71dc94d7541bc04f3685f54c39f1e2e69cc7d094f5d4365

Observation a0ebdb1e-6606-40e9-9579-de3d5f0a88b6 · outbound

This paper cites Tiny imagenet visual recognition challenge.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Tiny imagenet visual recognition challenge

Reference 29

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unresolved
no resolver link, observed 2026-08-07T12:01:28.132951Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:01:28.132951Z digest=sha256:865a4b09e5794ec2f82e5462bd053334b846f2954011e6043e4f37cb28b4e361

Observation 40b17063-1f1a-47ab-8686-545d1e9aef6b · outbound

This paper cites Preservation of the global knowledge by not-true distillation in federated learning.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Preservation of the global knowledge by not-true distillation in federated learning

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:01:35.799914Z

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=arxiv_source observed=2026-08-07T12:01:28.186039Z digest=sha256:59058d82f9194d51cfb72a0e11aa8d7c6c96dde6d5c36c8200d55668a2576cd7

Observation 0ce74682-ba80-4cdc-82e4-027338d0e383 · outbound

This paper cites Snip: single-shot network pruning based on connection sensitivity.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Snip: single-shot network pruning based on connection sensitivity

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:01:35.643587Z

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=arxiv_source observed=2026-08-07T12:01:28.224728Z digest=sha256:709e3a6b2eae4a5f5aadc608d424f977916494e04acc49ad5fb77f1f26871ec0

Observation 0dcdd45f-91aa-450f-b0f7-f5963d540436 · outbound

This paper cites Lotteryfl: Empower edge intelligence with personalized and communication-efficient federated learning.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Lotteryfl: Empower edge intelligence with personalized and communication-efficient federated learning

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:01:35.442612Z

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=arxiv_source observed=2026-08-07T12:01:28.279430Z digest=sha256:c2f88bb53c4b36c1198ae5a9b1d3e88862d8927c583aed5cf2dd40434bf02084

Observation 45f7760e-60df-47e1-b581-44950aa7f177 · outbound

This paper cites Federated learning on non-iid data silos: An experimental study.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Federated learning on non-iid data silos: An experimental study

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:01:35.296038Z

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=arxiv_source observed=2026-08-07T12:01:28.324668Z digest=sha256:e24c5431dbbce44e9cfc1935af545c18373c101b9b1c2b277faff8c377cf342a

Observation afc551cc-744d-4ec6-94c2-e3fd4e7f57ec · outbound

This paper cites Federated optimization in heterogeneous networks.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Federated optimization in heterogeneous networks

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-07T12:01:28.363095Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:01:28.363095Z digest=sha256:f1544cdf03ef95355b39a6e03f49cec9e89661dd26b02246b15be129d114431b

Observation 17ab0439-2651-4a5a-89c8-355573feee6d · outbound

This paper cites Ditto: Fair and robust federated learning through personalization.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Ditto: Fair and robust federated learning through personalization

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-07T12:01:28.414577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:01:28.414577Z digest=sha256:eeea5323d7117fa9ee30ddc2caa4e2a64a59887bbb16a06cb3256154a9f12606

Observation 394a42fb-1484-48f4-bfc3-0f83d0a9bc3e · outbound

This paper cites Fedbn: Federated learning on non-iid features via local batch normalization.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Fedbn: Federated learning on non-iid features via local batch normalization

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:01:35.127224Z

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=arxiv_source observed=2026-08-07T12:01:28.472697Z digest=sha256:33fcbd56f52318fa9fbc3e3ee55c66b584d84c56817816018a12a3e70ce239f2

Observation 911a8e7a-963b-445d-a997-9dcc4b0dce63 · outbound

This paper cites Ensemble distillation for robust model fusion in federated learning.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Ensemble distillation for robust model fusion in federated learning

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:01:34.967342Z

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=arxiv_source observed=2026-08-07T12:01:28.533884Z digest=sha256:b90f27c1a78661b8fa4eeca62fcfbfdf794c97a39e5e1bfd6159fef08588600f

Observation 059238b9-7e34-4759-93f9-25c0c9f5c2c3 · outbound

This paper cites More convnets in the 2020s: Scaling up kernels beyond 51x51 using sparsity.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity More convnets in the 2020s: Scaling up kernels beyond 51x51 using sparsity

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:01:34.783703Z

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=arxiv_source observed=2026-08-07T12:01:28.575955Z digest=sha256:dc11d15ad0d851052428a3e7347317d565a6fee91a63b94c1cc948ec41acb901

Observation 5d8b48bc-5294-4ba4-bbe3-cbc416966c71 · outbound

This paper cites Federated learning for open banking.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Federated learning for open banking

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:01:34.589057Z

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=arxiv_source observed=2026-08-07T12:01:28.614337Z digest=sha256:e97ed0377d9c8ecb2f61c4b500211f7672ee0c436057021869e6a092cdcb0170

Observation 1514cb90-b400-487a-8f54-926d508a740a · outbound

This paper cites Data-aware gradient compression for fl in communication-constrained mobile computing.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Data-aware gradient compression for fl in communication-constrained mobile computing

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:01:34.445709Z

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=arxiv_source observed=2026-08-07T12:01:28.656078Z digest=sha256:c7dc32e5f1a8a354bd49c2525c61a5814acea124c2835141782835ca4509ab49

Observation 1b374ad0-f8b7-46a6-a377-13ecd2cd6d68 · outbound

This paper cites Layer-wised model aggregation for personalized federated learning.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Layer-wised model aggregation for personalized federated learning

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:01:34.312365Z

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=arxiv_source observed=2026-08-07T12:01:28.676494Z digest=sha256:7fed7c23aa340eba06e0372b460002e360a30087f6d6c84d615a96b405bb9715

Observation 94ff3aa7-7dd1-4983-9dbc-1690f71e98c2 · outbound

This paper cites Three Approaches for Personalization with Applications to Federated Learning.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Three Approaches for Personalization with Applications to Federated Learning

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-07T12:01:28.717182Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:01:28.717182Z digest=sha256:21805a65968cbedf35c03dc4d6aed12f64b5c7dfb08de862fecf7642a6545be0

Observation 339c78cd-08f1-4145-864c-132f315af4a8 · outbound

This paper cites Communication-efficient learning of deep networks from decentralized data.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Communication-efficient learning of deep networks from decentralized data

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-07T12:01:28.768824Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:01:28.768824Z digest=sha256:03d547a7618a12eae97af7f880f7ec8013a45a59f531b81a62f1738e396c78cf

Observation 5be6f8fb-575b-4202-b674-6edd31f5f66e · outbound

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

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Communication-Efficient Learning of Deep Networks from Decentralized Data

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-07T12:01:28.798644Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:01:28.798644Z digest=sha256:fbf509eb0f9e7c868acf4ac41a998618199c2637f985054f6c13899f0c2f7520

Observation 28352342-8126-40c6-8f27-3a2131208185 · outbound

This paper cites DOCS : Quantifying weight similarity for deeper insights into large language models.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity DOCS : Quantifying weight similarity for deeper insights into large language models

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:01:34.136773Z

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=arxiv_source observed=2026-08-07T12:01:28.857132Z digest=sha256:e0c17b67edd06c0a8e7d62baece468e77f38f40757f53b5a604cef420c3a7985

Observation 5761dd9b-773a-49ae-b1ad-cfbf82aa24ea · outbound

This paper cites Linear convergence in federated learning: Tackling client heterogeneity and sparse gradients.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Linear convergence in federated learning: Tackling client heterogeneity and sparse gradients

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:01:33.966326Z

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=arxiv_source observed=2026-08-07T12:01:28.911827Z digest=sha256:3d0af3ed564f5075fb74d727c8e2bd51dbc06fc4e40983f845d9db21eecfaebb

Observation 98f01d81-f0a8-4848-9fc5-9848a5bc71a3 · outbound

This paper cites Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-07T12:01:28.949399Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:01:28.949399Z digest=sha256:041105fd37f8f5292a47d91c8529557ca9c72a1e2e5984d382029750e2c5c7ee

Observation d3d5276f-8452-47f8-9f47-4ac556017f66 · outbound

This paper cites Federated learning for smart healthcare: A survey.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Federated learning for smart healthcare: A survey

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:01:33.839823Z

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=arxiv_source observed=2026-08-07T12:01:28.983211Z digest=sha256:26d9a948d0ee3acfb3b8c614eae3b69435ae6057d00e46bfb9e74615ce9d8ade

Observation 50b76e04-cea2-46d9-8e2f-d289f803a849 · outbound

This paper cites Fantastic weights and how to find them: Where to prune in dynamic sparse training.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Fantastic weights and how to find them: Where to prune in dynamic sparse training

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:01:33.692341Z

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=arxiv_source observed=2026-08-07T12:01:29.054020Z digest=sha256:341c245d7329af4b975c82103a75d7dac1127f51ae14ce6d617ac9b6f5d7b279

Observation 170bf5f2-bbf7-491d-871f-27f4fe7e87e7 · outbound

This paper cites The future of digital health with federated learning.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity The future of digital health with federated learning

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-07T12:01:29.103827Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:01:29.103827Z digest=sha256:3700fa6b8d69319ba232e8421bef8d1724b5fdc7129baa6bed2b1d6a0b84a505

Observation fcfdbd23-c7e3-41ab-8aaf-548fa913f3d3 · outbound

This paper cites Privacy-first health research with federated learning.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Privacy-first health research with federated learning

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:01:33.560715Z

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=arxiv_source observed=2026-08-07T12:01:29.171148Z digest=sha256:48041ad4b702bbd78a42cdd3fb3129c74d48da66ea22ce2b8c2834273a77d2f7

Observation f901724d-4b21-4520-9fc8-df5c7ad158ba · outbound

This paper cites Very deep convolutional networks for large-scale image recognition.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Very deep convolutional networks for large-scale image recognition

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:01:33.390586Z

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=arxiv_source observed=2026-08-07T12:01:29.215033Z digest=sha256:99472da84cdccb273056bbe7f9e3598f30dc839fb09ea941d0d88d1caf49f192

Observation 8afc7de2-7fb6-4001-9897-d1a1da6d9ef9 · outbound

This paper cites Federated reconstruction: Partially local federated learning.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Federated reconstruction: Partially local federated learning

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:01:33.302530Z

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=arxiv_source observed=2026-08-07T12:01:29.256955Z digest=sha256:6363572f8221308fe2f1e734d15ad526fde3843e7804a646806d88b78947248c

Observation 45075c7c-0ee8-4568-8dad-54c7f18c95e1 · outbound

This paper cites Federated multi-task learning.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Federated multi-task learning

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:01:33.108719Z

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=arxiv_source observed=2026-08-07T12:01:29.311510Z digest=sha256:22be414bec31eac4c05e52bf293d255398ca72ffa6e48515bd44ddfe538531cd

Observation 4201c5af-f70c-47e4-a2a1-8091817a4b87 · outbound

This paper cites Fedselect: Personalized federated learning with customized selection of parameters for fine-tuning.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Fedselect: Personalized federated learning with customized selection of parameters for fine-tuning

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:01:32.970855Z

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=arxiv_source observed=2026-08-07T12:01:29.394533Z digest=sha256:76f7b6f68510aa5960c918607e1601a2958d9a06d7011b1c19eaefe68041adf8

Observation 394183c3-786c-4669-9605-db470dc6542c · outbound

This paper cites Towards personalized federated learning.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Towards personalized federated learning

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:01:32.799625Z

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=arxiv_source observed=2026-08-07T12:01:29.453487Z digest=sha256:cdee126d8b641de0a7bb386c27700a283e89ce91285616bc5e28b12bc5a3bd10

Observation a5f29e82-fe72-42c8-adef-04610337855f · outbound

This paper cites Fedgen: Generalizable federated learning for sequential data.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Fedgen: Generalizable federated learning for sequential data

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:01:32.624482Z

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=arxiv_source observed=2026-08-07T12:01:29.482166Z digest=sha256:5b6020ea7c59ad567dc2fcbf35058241d9c1c77be5c52f045685b75fd1f959cd

Observation 4fa4556a-c74c-4cc0-ac11-22a03d7698e1 · outbound

This paper cites Gradient sparsification for communication-efficient distributed optimization.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Gradient sparsification for communication-efficient distributed optimization

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-07T12:01:29.538718Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:01:29.538718Z digest=sha256:f30a75ac96d859883f9718c8c2e6408bd0b01d44c58bfbd7da480b59d19c45fa

Observation 2c357a6b-4072-4ea0-89d1-f6d89a6c7020 · outbound

This paper cites Federated dropout—a simple approach for enabling federated learning on resource constrained devices.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Federated dropout—a simple approach for enabling federated learning on resource constrained devices

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:01:32.494715Z

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=arxiv_source observed=2026-08-07T12:01:29.640038Z digest=sha256:6731c5147ecdc02e59a3a2f7b8dd2a2de552a17edd5ab0f9f6c519b47f7b5464

Observation 26f51148-c2e0-4952-a118-c1866d78383b · outbound

This paper cites A survey on federated learning: challenges and applications.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity A survey on federated learning: challenges and applications

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:01:32.356201Z

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=arxiv_source observed=2026-08-07T12:01:29.694276Z digest=sha256:c75db6f95aae0ddcbcd2ca2c655fb596ac6d8aca0cd8128c81b93b5fe3b64cf4

Observation 2db56f38-236d-4217-a9e6-dfc95ee7d3ce · outbound

This paper cites Dynamic sparse training versus dense training: The unexpected winner in image corruption robustness.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Dynamic sparse training versus dense training: The unexpected winner in image corruption robustness

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:01:32.212231Z

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=arxiv_source observed=2026-08-07T12:01:29.750223Z digest=sha256:a655d6d91cca435ab2fa2d01ea6117e48c32dc55c2b98d7647c148839802dbc7

Observation 0d39e952-8c6d-4b5d-9b27-bf5df01a8f5c · outbound

This paper cites Bold but cautious: Unlocking the potential of personalized federated learning through cautiously aggressive collaboration.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Bold but cautious: Unlocking the potential of personalized federated learning through cautiously aggressive collaboration

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:01:32.046871Z

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=arxiv_source observed=2026-08-07T12:01:29.862479Z digest=sha256:6aa236aa47193b9a8d2d0226997ed1d3121157e958c06c29390dd3bcb34de4de

Observation ebaf4a79-ae09-423a-97a5-7606e617f3d5 · outbound

This paper cites Dynamic sparse network for time series classification: Learning what to see.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Dynamic sparse network for time series classification: Learning what to see

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:01:31.922998Z

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=arxiv_source observed=2026-08-07T12:01:29.945925Z digest=sha256:3f543738f943ec1ad2f02f84e6686cc4e188914a17b63583493cdc1307d35162

Observation 04477e81-fd87-403c-8547-bbe2fd59fd40 · outbound

This paper cites Federated machine learning: Concept and applications.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Federated machine learning: Concept and applications

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:01:31.690177Z

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=arxiv_source observed=2026-08-07T12:01:30.001354Z digest=sha256:95f675be9825a7a4455995548ba1ed43a995771a669768f8f42e61890d04e7a3

Observation 08924eeb-62a6-4f1d-8347-ec47fef78bb9 · outbound

This paper cites Fedmix: Approximation of mixup under mean augmented federated learning.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Fedmix: Approximation of mixup under mean augmented federated learning

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:01:31.440431Z

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=arxiv_source observed=2026-08-07T12:01:30.005155Z digest=sha256:605392a4233a9981ddd38013648173c4fdf1abc69d39a61dd8df42142a1bacee

Observation d9998c98-518e-46c7-8ff2-483d3d69d3f2 · outbound

This paper cites Salvaging Federated Learning by Local Adaptation.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Salvaging Federated Learning by Local Adaptation

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-07T12:01:30.082217Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:01:30.082217Z digest=sha256:6ffc60250e11ec4cc14e084e86e6070752bde21cd61d2213e7ba06682db5fffe

Observation f9d74c3b-0664-4d26-a7c5-300c1a912aec · outbound

This paper cites What do we mean by generalization in federated learning? In International Conference on Learning Representations, 2022.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity What do we mean by generalization in federated learning? In International Conference on Learning Representations, 2022

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:01:31.325541Z

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=arxiv_source observed=2026-08-07T12:01:30.205912Z digest=sha256:de77bbae65cf1de775b4fafd73b0e6241d278ceee327b06bffc021c43fc5a3b4

Observation add2da19-5ed6-46a5-8496-33ec7c0d7025 · outbound

This paper cites Fedala: Adaptive local aggregation for personalized federated learning.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Fedala: Adaptive local aggregation for personalized federated learning

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:01:31.071637Z

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=arxiv_source observed=2026-08-07T12:01:30.291938Z digest=sha256:a8f2bc81f1f8955823ddec251c04e8f341843d57f23da20820350d197f50c0a3

Observation 5077a07a-0e6f-4e73-97c7-c00ba6c20595 · outbound

This paper cites Parameterized knowledge transfer for personalized federated learning.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Parameterized knowledge transfer for personalized federated learning

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:01:30.861352Z

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=arxiv_source observed=2026-08-07T12:01:30.333731Z digest=sha256:a97b8beed77a621a4d0574734c403517165abeb8143bb903549133f37df11f35

Observation 07221ebc-8494-4dad-a89d-46d3e020f806 · outbound

This paper cites Federated Learning with Non-IID Data.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Federated Learning with Non-IID Data

Reference 70

Resolution
unresolved
no resolver link, observed 2026-08-07T12:01:30.460023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:01:30.460023Z digest=sha256:6cf9b52dd47e73a0cf7acc20d25cf1c77cf6ccae21da4416f5e135bcefa4c7b5

Pith citing papers

No inbound Pith citation observations are available.