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Paper Citation Record · LEDGER

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

As of 10 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 2026-08-09T06:31:02.800959+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

70 of 70 outbound references displayed

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  • verified fuzzy49
  • unresolved21
  • parse uncertain0
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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

Unavailable: canonical work link unavailable.

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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

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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

Resolution
verified fuzzy
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Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T12:01:26.723592Z digest=sha256:2e841ef0130d2a8a5f1ab73d6b651a259233cc7ede4c9f4200dcb6220af8fc07

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

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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=arxiv_source observed=2026-08-07T12:01:26.815025Z digest=sha256:7db8869591e031c2efb59ae6fd0da2a2a0d356703f59c57560b4f3c17785d590

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

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Source-reported events for the cited work

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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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T12:01:26.949521Z digest=sha256:e519bbd0a7654b08c0269cebcd2b0b211548cd77e7f92896c3bfae919d2eeabc

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

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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=arxiv_source observed=2026-08-07T12:01:27.005979Z digest=sha256:da85ebe8a1c598ad18d9d877dddd5574b3f8959b77a441818cacfa7b78a40f0b

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

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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 2026-08-09T06:31:02.800959+00:00.

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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 2026-08-09T06:31:02.800959+00:00.

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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

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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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T12:01:27.215567Z digest=sha256:d1c611f8e367ad507a21eaa55b8c8c6c17fcd7e9c092f87b275b958915f0469b

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

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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.

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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:bfa8d611493493347dd9ecffa39bd110625fb0f1386b1d743663faabf637563d

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 2026-08-09T06:31:02.800959+00:00.

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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
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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=arxiv_source observed=2026-08-07T12:01:27.423364Z digest=sha256:f7b69d89000969b87ffc6770a39652f9d98a906ffd51474c2100284941bfdd65

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
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:01:27.475372Z digest=sha256:46647423cf138693eceb98ea1c6210d30da03dbd1bbe02270cb3043b58c73516

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 2026-08-09T06:31:02.800959+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
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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.

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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 2026-08-09T06:31:02.800959+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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Unavailable: canonical work link unavailable.

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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
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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.

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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

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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 2026-08-09T06:31:02.800959+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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:01:27.959097Z digest=sha256:3c2d1286aa73761b7f11a8fa4ffc98fe9fd0a3e3a0c0a24923aa716a39134803

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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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=sha256:60b80ba94f89f24b21d925c6048f913a7b4dc81a22f6d82a9f3abc6272b30aeb

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T12:01:28.041244Z digest=sha256:40647ac66c85067b62579218e9657e5e60e00a7ed403594781a62b7f0b943f5b

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=sha256:6d3a0626b7ff187f38a9d28ce717d9f080c8649a22990ca3f59dd40a40d1e057

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=sha256:4d7b421a4ccf839d63042d460247ab1d09f90dacf8ab1a2847d3ac432d0aff2b

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T12:01:28.186039Z digest=sha256:815b7b3521d2a3db1351ffad4ea76589e419b4a28a81b190868f807920253a09

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T12:01:28.224728Z digest=sha256:bf960ac3f6d8570b704efb3de42bb0f134908c86211d71eea5c0ca00b64edebe

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T12:01:28.279430Z digest=sha256:da8568f072e70c8825d756115bf0dd5c2045037e35fe486e29ecb47540d02f71

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T12:01:28.324668Z digest=sha256:11b4ca4cb0a9567d5d255616b02cab2fbaccb629cd593bc2a9fed1106050ee2b

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:f29951f979e30b6ac0484c95ce0a519f1238e87a5789614a563313df54b1e1f4

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=sha256:7ce8d801286d6d59e609855bfb4575f206af97e597acfe6f24ea8f25bd523644

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T12:01:28.472697Z digest=sha256:bcbf663e1bddaf9a261eea57902cca29513f0e3941985e29d9c0988247918b8e

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T12:01:28.533884Z digest=sha256:aba00478cd2f9f359370ce4230e0ffca5b86739e722ee75fa20657c7ecdc2583

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T12:01:28.575955Z digest=sha256:509739fd68ee0d50e71e7d4e18133ca7979fb872c16d26bad10ba7b754e3d0f3

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T12:01:28.614337Z digest=sha256:cca0750d19a3308aed754d61143293abedfc584a22b680c5a13ea2e4183431b0

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T12:01:28.656078Z digest=sha256:b09dc3e3c37fa88c4ebc36f89057755ee28f1cd2f9b9dc631623e248c4ecf878

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T12:01:28.676494Z digest=sha256:9489b73e26db609774f82a84861ab3ce247a0783860847001c0f1714809aaf0a

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=sha256:668fef655f691c2fd47b10ffdd6c905dfd39b2ff2ad9e049560a0203b8599352

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=sha256:1ec0e0426d721e91f44f80a08be9f57fbca2021ae9addc48795b8e4e9311cb62

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:afaf029f0c3f420c2716a6817a8790466874a3cdfbd8b527b9e0415496e89c5d

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T12:01:28.857132Z digest=sha256:ac20c5a221bbeb01292922424fef74b6c7218f7529494697ed13ad62a7ad8fca

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T12:01:28.911827Z digest=sha256:9f547de5de7d6b919f76e1c14d6e5756af8a80814599efdbf606804e1d22e515

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:e764eb39ee05bed16ea96868fa4de1eb66dfd7c684aadab4d76b8e13323a2297

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T12:01:28.983211Z digest=sha256:8c2daed0f518b531f1fdea90ee22f287d2ad570aa24c1bde7f223d5f31f20b61

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T12:01:29.054020Z digest=sha256:81365353b6ed5e398604ff0294947150202289b671f1607f2985a0ef55238e34

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:b4fbf15ba706bc33d9f87b3cf99a1fcdc1a0f424549e12c664b1d63642987a49

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T12:01:29.171148Z digest=sha256:2a01dac92431a59cd52a0ee336640e89792ff5f2df2c7c73f14e7cac7fd08f14

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T12:01:29.215033Z digest=sha256:1a8f8b5b64da5de6bb0873724295178dff177feb38e4b04fe3cba36611c11139

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T12:01:29.256955Z digest=sha256:0b89f0864ad845ebe95b8c7012930fcc2e3114a1dc09e8dd50e7ce781fc7329d

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T12:01:29.311510Z digest=sha256:163326731f5048a4afc6c50ad553b95ce641e5ea13dfa0b13a0f7ee726ff7df0

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T12:01:29.394533Z digest=sha256:89d1327c0621c8c49fd726ed0b059f501d2800ad62a1de695a982ce4e981b881

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T12:01:29.453487Z digest=sha256:d587d522fa3477596333ba450c09ec678af484eb5321a8ef1c896121445b39d9

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T12:01:29.482166Z digest=sha256:929a37059acdd158d08d1af25849d2ab781c824f2a4e901b652ae8eafffea1cc

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:f8c7c4e4aefbff1c2c8f682c811e8dc0c1ba7b1ce3db15d321a11b91c0d46575

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T12:01:29.640038Z digest=sha256:cb0cb105de9f8a11469ed7ddd011b17d6b750fef3d5a80e6c39675c803d62e7e

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T12:01:29.694276Z digest=sha256:f82d80dcf7fbac9e68508947064a1b461a1d94114ccf1b079d7521f7b44e5525

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T12:01:29.750223Z digest=sha256:546b3250430e18daed0a7d8dfac5d64962803743584e5a58d161e67121d653f0

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T12:01:29.862479Z digest=sha256:415aff3f826902723033d3e58e096d09bc1beaa5f5a857a17cfc1f21621c6451

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T12:01:29.945925Z digest=sha256:e93f619a856d18c4cdbb7589a2db6907ab2a2417a4a12ef3cd05603d93a98d12

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T12:01:30.001354Z digest=sha256:3e6cbd58ac13213f8446cd971e624f2eab7bdf9adecd4a0f914c4dcb97d1d57d

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T12:01:30.005155Z digest=sha256:2d267a661c476e7a3b0546b5c4efb9aba6fa465ed6e673967e2e69f50970be26

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=sha256:0aded99fb59dfa884856467065b3741b9c08c8bdc2427957ec954c391d49de02

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T12:01:30.205912Z digest=sha256:1dadf0169dac9f5e6cef64496382dae3984b456567b47017b6377aa18158af54

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T12:01:30.291938Z digest=sha256:fdd7ac6dc10bdae74b269b393b86fa1ec11edc306615d69d38825d1341d00b82

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T12:01:30.333731Z digest=sha256:7fbbc56af6385b3d40f551f374c3101f25d10d19642718f6a748fb26c44ed1d7

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=sha256:5d498d56e122eb2121cbc82ffe236bc9e39736c8ea91a7bf47bb92c24d0f1c35

Pith citing papers

No inbound Pith citation observations are available.