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Paper Citation Record · LEDGER

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data

As of 20 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 0 inbound Pith citation observations for arXiv:2607.02447.

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

pith.paper-citation-record.v1
2607.02447 v1

Coverage vector

measured 52 of 52 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-03T16:29:09.303242Z

measured 52 of 52 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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

52 of 52 outbound references displayed

  • verified exact3
  • verified fuzzy41
  • unresolved1
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch7

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 218a9100-4cc1-4af5-9736-1168fd28cc16 · outbound

This paper cites Proceedings of the 36th International Conference on Neural Information Processing Systems , pages=.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data Proceedings of the 36th International Conference on Neural Information Processing Systems , pages=

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T05:30:43.826627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:3508822f48357726fffcf8e26de3e25acad4c96989ced0a54a8686db8d4fb868

Observation 10429905-f6d7-4e74-afc2-e5d625d0d354 · outbound

This paper cites Scaling Language Models: Methods, Analysis & Insights from Training Gopher.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data Scaling Language Models: Methods, Analysis & Insights from Training Gopher

Reference 2

Resolution
metadata mismatch
local_arxiv, observed 2026-07-03T16:38:39.818176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:77c72515f24e31d72bdbacece3811d6ef9dbb92b25ba637f9b6956021992b482

Observation b7e7bb35-35de-45ec-818b-e286e6102337 · outbound

This paper cites Does Learning from Decentralized Non-IID Unlabeled Data Benefit from Self Supervision?.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data Does Learning from Decentralized Non-IID Unlabeled Data Benefit from Self Supervision?

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-07-03T16:38:39.824422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:1154d5e206c4444e92f1a796fd9067a8cfb4d5312beec1234dc0d96673c0898f

Observation c090e2a6-16c5-4d5d-80bb-711a67d3d226 · outbound

This paper cites IEEE Transactions on Pattern Analysis and Machine Intelligence , year=.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data IEEE Transactions on Pattern Analysis and Machine Intelligence , year=

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T05:30:43.834579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:b889b2c45bc98f2229de87efcde589591aa4e49eafdde2ae56425483d2e0dd34

Observation be44f6b0-aa53-41d1-81d2-99e4bfd7c747 · outbound

This paper cites IEEE transactions on knowledge and data engineering , volume=.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data IEEE transactions on knowledge and data engineering , volume=

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T05:30:43.857353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:5983700b775e63a48f8e206ffbb3234d10fc2bb082ee5ea673b2f310b4e56214

Observation d6defa13-1493-499e-9025-74374d81d962 · outbound

This paper cites International Conference on Learning Representations , year=.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data International Conference on Learning Representations , year=

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T05:30:43.862560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:9d8e737b0e7b46873b72b84999b5fba809445a60db008914535753fda06c46b5

Observation 20b0d59a-651c-4347-9871-16ffffa4a7de · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data Advances in Neural Information Processing Systems , volume=

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T05:30:43.839411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:1406371c6f807095b7e5cca1e7b498b27aec0488a8ce4181464fa999999b6f56

Observation f88eefa3-8062-496e-b9d3-296a73ee9621 · outbound

This paper cites Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , pages=.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , pages=

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T05:30:43.818104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:f3791ad6f88764bbb3f8073c49209ccd96847d613a8468978447b73ed494d837

Observation fc2d3a70-2f17-404e-af83-49b42413fec7 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data Advances in Neural Information Processing Systems , volume=

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T05:30:43.820097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:21de94fcaf72aef5865e9cf66c8243c3c0cf533289f70025c8b4869388cba7a2

Observation 61904a08-db51-4013-9061-5d0143b0fa1a · outbound

This paper cites Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages=.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages=

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T05:30:43.805175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:27e41c80b9d193e273cfaeb959841974e15da9990ba000af7d1dafb3ac53ff5b

Observation e8c46c1f-1e78-4a72-b48f-a4716475f879 · outbound

This paper cites Artificial intelligence and statistics , pages=.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data Artificial intelligence and statistics , pages=

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T05:30:43.794792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:81eacca5d0522002415a351995e68f93806f41dfb2852915e71236c48b35b516

Observation e5d70473-9ffa-43eb-a1c9-bc6791f0539c · outbound

This paper cites 2019 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW) , pages=.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data 2019 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW) , pages=

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T05:30:43.814111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:f364b68cb491f30780bbeef59d92a4bce2e2cafe6196366e533c00f51331416a

Observation b5bcae62-4d01-480d-8eae-7101f9848c27 · outbound

This paper cites IEEE Transactions on Parallel and Distributed Systems , volume=.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data IEEE Transactions on Parallel and Distributed Systems , volume=

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T05:30:43.815983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:728eb8239a782676c3113bd2d0389a8703aa6772072851cf0da669c3dbd0277a

Observation 50acbb66-8251-46ad-b40b-a2ef9d2a10d4 · outbound

This paper cites 2024 , eprint=.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data 2024 , eprint=

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T05:30:43.817828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:cb111bfa19e89810889762cd42983d6365e80f3ff7f17226fa36c04325016e3a

Observation 49ccaf9d-05fc-4163-96a3-2098d5ea5f6f · outbound

This paper cites Neurocomputing , volume=.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data Neurocomputing , volume=

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T05:30:43.811024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:7f14be4711db25d70a3bc4fc3d9f1c76c52ef91148755816919a2348ebb90c40

Observation 462d9e4e-c5a4-44f6-bc70-11abe1bd14ea · outbound

This paper cites Proceedings of the IEEE/CVF International Conference on Computer Vision , pages=.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data Proceedings of the IEEE/CVF International Conference on Computer Vision , pages=

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T05:30:43.868338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:2d60203015f81f131d59d032d4c7f1de7c916cf88d4e776b62ae03026f45210a

Observation b53d153a-b29d-41c7-afb4-3384c8b82587 · outbound

This paper cites International Conference on Learning Representations , year=.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data International Conference on Learning Representations , year=

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T05:30:43.804876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:f05d98abef68edaf770cd3289a812e178b33058bb2633a07338af05c50ec76e3

Observation 50d03d90-259d-4c7b-b146-81763b14a37c · outbound

This paper cites International Conference on Machine Learning , pages=.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data International Conference on Machine Learning , pages=

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T05:30:43.880831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:245d11948a005e1ddaa58ae4b6850da69f4c4d7460af69e54ac71e220db72c33

Observation f5f5e2bc-a733-4324-b84f-3c75edb12b0e · outbound

This paper cites Proceedings of the IEEE/CVF international conference on computer vision , pages=.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data Proceedings of the IEEE/CVF international conference on computer vision , pages=

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T05:30:43.799210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:7f5d6d3605c0728d030a76a6a43213358c1be1843fd60358592882a9dd5df12d

Observation a3eef3e3-4849-48e9-be30-0bb72b5056f9 · outbound

This paper cites FedSC: Provable Federated Self-supervised Learning with Spectral Contrastive Objective over Non-i.i.d. Data.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data FedSC: Provable Federated Self-supervised Learning with Spectral Contrastive Objective over Non-i.i.d. Data

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-07-03T16:38:39.829132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:f1846812e4fbf5594b4320682ba29963563039acb5dffb6ca7f9b1c03183150b

Observation 710c7a57-dd36-4f1e-81f7-b727e58c8646 · outbound

This paper cites International Conference on Machine Learning , pages=.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data International Conference on Machine Learning , pages=

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T05:30:43.862353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:5b99aaa701d4fab427176f4bbf9e3418b8d6d439d93ebb9d14998be53bda5bee

Observation 4fd85f91-c0d2-472f-bdca-c9edcb1c588b · outbound

This paper cites Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , pages=.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , pages=

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T05:30:43.853456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:161bb37f0cc85eb47999025bb1bfcc67d6bb5c32e3152ad08f7a88eeba3414ec

Observation 679246e9-fcd1-4269-b27f-c258fd2a3bb5 · outbound

This paper cites BEiT: BERT Pre-Training of Image Transformers.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data BEiT: BERT Pre-Training of Image Transformers

Reference 23

Resolution
metadata mismatch
local_arxiv, observed 2026-07-03T16:38:39.823845Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:2e80012c5d8dfed2158a247978d4f00a46aca03127a80353e3b7f89e5654e3e1

Observation 42823ef4-528c-4736-94fe-a0da930822a5 · outbound

This paper cites iBOT: Image BERT Pre-Training with Online Tokenizer.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data iBOT: Image BERT Pre-Training with Online Tokenizer

Reference 24

Resolution
metadata mismatch
local_arxiv, observed 2026-07-03T16:38:39.826234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:5d4b3ce05c7396374d7a641f4357c95a89004cbe71c8923a1a34427bf17ac991

Observation 52c2bc8c-3789-4e73-8df9-c84bd89f6a4b · outbound

This paper cites Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , pages=.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , pages=

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T05:30:43.845124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:b7385e4aab7f61ea9ee0c5646ee14243304e9aae466cb599f2bf8020104d9b87

Observation 60d9f874-0456-47a2-8ba5-a0d59f0aff53 · outbound

This paper cites A Mutual Information Maximization Perspective of Language Representation Learning.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data A Mutual Information Maximization Perspective of Language Representation Learning

Reference 26

Resolution
verified exact
arxiv_id, observed 2026-07-03T16:38:39.827187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:f2fb0627b9988faed9e0358fc5364089fd48cb937515666ff3c36672855cfeb9

Observation 1eabdd21-3b58-4926-bfe8-87b3855075f4 · outbound

This paper cites Acm computing surveys (csur) , volume=.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data Acm computing surveys (csur) , volume=

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T05:30:43.830722Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:7b6da3e8954ca09af5e3ae49927a61726d9504073db8804e6bc3dd75694675c6

Observation 6186e40c-3db1-4f90-b2d8-7fcf672c9efe · outbound

This paper cites Knowledge-Based Systems , volume=.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data Knowledge-Based Systems , volume=

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T05:30:43.822308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:7f3a244a2a8ebd134175ac68e67445481e39bf5593744ce6fa7bc7382664689f

Observation e9dc9370-3b5a-4de4-9f64-40917a5a9b76 · outbound

This paper cites IEEE Communications Surveys & Tutorials , year=.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data IEEE Communications Surveys & Tutorials , year=

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T05:30:43.828506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:49a4118eb012e8638258770afeb347486bebac249c311a191d46a8b37a205641

Observation 04d1b0e3-2ddb-4e06-9484-ed1cd621b057 · outbound

This paper cites Journal of Parallel and Distributed Computing , volume=.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data Journal of Parallel and Distributed Computing , volume=

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T05:30:43.803320Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:0e246c57aa1579513ae93b796101202e888d339d695713105273246f418e1f48

Observation ea526621-eaac-4fa6-bb38-bf1f7709beae · outbound

This paper cites Advances in neural information processing systems , volume=.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data Advances in neural information processing systems , volume=

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T05:30:43.807110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:7c824e1b2099698825f864fee036233290121f45a139d41fe239e69b2853b3e1

Observation a67407d3-7cdb-44c5-bd23-ade6f29c2242 · outbound

This paper cites 2009 IEEE conference on computer vision and pattern recognition , pages=.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data 2009 IEEE conference on computer vision and pattern recognition , pages=

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T05:30:43.866342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:4dc521a563b4c9e482df39fdd2d06b9fe9f05a981ef5429f0c0ee7fba56dd218

Observation bdc8f842-729d-4e99-ac08-0538e9d95c39 · outbound

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

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification

Reference 33

Resolution
metadata mismatch
local_arxiv, observed 2026-07-03T16:38:39.812986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:90f5343e0676e9d504c572d158501f9a24bd0026fd9f510573e22374dec7841a

Observation 67bf40c9-7631-47ff-a8a9-189e073ffaab · outbound

This paper cites 2009 , publisher=.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data 2009 , publisher=

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T05:30:43.864529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:d7759d7d8e4876b17251663a3b8dbc753835202a995e60d25ba58f0a98872a52

Observation 74b35329-db22-4e6c-bd0d-20d744f0589d · outbound

This paper cites an unresolved cited work.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data Unresolved cited work

Reference 35

Resolution
unresolved
raw_fallback, observed 2026-07-05T05:30:43.816191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:2d5bcf1fb8085f187531e0b118340266978b83843800f046eeae0930f8cc75ea

Observation c5e6e5c7-593f-4e56-b9d0-11e76537791c · outbound

This paper cites Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , pages=.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , pages=

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T05:30:43.870593Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:32178a7f5e8a6d759f86b88fcd0711b0dadab159a507e6c61caddd9fbbdb3107

Observation d5f0badd-2fcb-47ec-8b67-e8718a9586fa · outbound

This paper cites International Conference on Learning Representations , year=.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data International Conference on Learning Representations , year=

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T05:30:43.872656Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:be4a25ffed64ab998fc84555a45af75ddea7c941f048053ba652210c5b1b37c6

Observation d89220b8-f7bb-497f-8692-8fb167d20de5 · outbound

This paper cites Advances in neural information processing systems , volume=.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data Advances in neural information processing systems , volume=

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T05:30:43.857902Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:4341332bfce19dcf7dd7d8f49e55a2a72721d51691d224e31e6a5c33b2b48b71

Observation 1d93f029-1ceb-41cd-ba84-70b946b28452 · outbound

This paper cites Advances in neural information processing systems , volume=.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data Advances in neural information processing systems , volume=

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T05:30:43.840497Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:e26489fabc2631f3c4bf1d7dca5cfed231e48e81b7e60e2173c374ad4ba8e8d8

Observation 89f08d23-599f-4bd8-80b1-dc525581ad34 · outbound

This paper cites Psychometrika , volume=.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data Psychometrika , volume=

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T05:30:43.836416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:7c45f23d13287dfb11910f311c595c1b722ff4d0e84d1987d4e695ac61c3e0ab

Observation a6712545-d35c-45be-8922-ed323761a473 · outbound

This paper cites 2018 , publisher=.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data 2018 , publisher=

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T05:30:43.853606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:c76a5669d4825d09dbfbb52c3280364b2807bf2d06697191e0c2b4f19945948a

Observation 010502c4-e49a-4aff-b159-c825753da7b7 · outbound

This paper cites FedMAE: Federated Self-Supervised Learning with One-Block Masked Auto-Encoder.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data FedMAE: Federated Self-Supervised Learning with One-Block Masked Auto-Encoder

Reference 42

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T16:38:39.821273Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:1f50de75e7c7c60a69e74dd39b3d0b9269e7494e39bdd285860dce803b6b63a1

Observation b63be931-7026-4163-bf9c-fb7de8604bc2 · outbound

This paper cites The Journal of Machine Learning Research , volume=.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data The Journal of Machine Learning Research , volume=

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T05:30:43.855716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:6636a30491e1d91210b92983f696774b41c78c59d59b3ec4e1784613009a02e4

Observation c85c361a-f45c-4a2a-a825-c29b3e155e07 · outbound

This paper cites Advances in neural information processing systems , volume=.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data Advances in neural information processing systems , volume=

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T05:30:43.860177Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:63d1b150e2d0b9c8c17eddb28cb1b59a199a102fada5aa0fd30a36cfadb5326b

Observation 1fd64833-477c-448f-b2af-1f845d2a10ac · outbound

This paper cites International conference on machine learning , pages=.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data International conference on machine learning , pages=

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T05:30:43.851726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:7ac76486c45baa8b8e4ea6a82148f3221d2431c47fc5e5e9c929a12ba48f2bff

Observation f767b629-be8a-483a-b893-e6295ac1f800 · outbound

This paper cites Expert Systems with Applications , volume=.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data Expert Systems with Applications , volume=

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T05:30:43.841386Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:ed723e05cf913813d0dc44754cead8ca6c0a861180c879191e7e4d5662bd7ace

Observation 9c6d0802-ca48-485d-8b17-c3dcf328a5b7 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data Advances in Neural Information Processing Systems , volume=

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T05:30:43.843214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:1bef77166c6a8aee825954b2af385b4cd3f42654385fd6984a4237f4532bdf78

Observation 4a039ba9-c0b2-4d49-b34b-1bb851117608 · outbound

This paper cites International Conference on Parallel and Distributed Computing: Applications and Technologies , pages=.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data International Conference on Parallel and Distributed Computing: Applications and Technologies , pages=

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T05:30:43.849669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:fe05b0133171524eed360514193d70c5e264947d6630cc8ef75a6e018aaff014

Observation 4b1a8896-e06b-432d-b3e8-3fa137dabe6e · outbound

This paper cites Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages=.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages=

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T05:30:43.847383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:c86e89fe524cbfa265caf1803f9a75861f0ec89bfdb6a6a3e1975902ae82a6c1

Observation 71b973eb-36e3-44ff-bc5a-404473641162 · outbound

This paper cites UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction

Reference 50

Resolution
metadata mismatch
local_arxiv, observed 2026-07-03T16:38:39.815826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:b69e8081c5e6b30cc08b68b1e50bd1fe48fef3239d028b16f3f336d47775f14a

Observation a94b8020-b8ba-44dc-98d0-02a5a712f8e7 · outbound

This paper cites Learning Differentially Private Recurrent Language Models.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data Learning Differentially Private Recurrent Language Models

Reference 51

Resolution
metadata mismatch
local_arxiv, observed 2026-07-03T16:38:39.831751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:c51af7d80b17e5b61bda05b35c1500365504dda563ba23cf33450ca6ce890e3e

Observation 5327338f-a5da-402d-a8ee-fe788347af57 · outbound

This paper cites IEEE transactions on information forensics and security , volume=.

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data IEEE transactions on information forensics and security , volume=

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T05:30:43.882900Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-03T16:29:09.303242Z digest=sha256:a8d5cdbbe849349c721568d158396671f6b0bcb791efd1cea5c2bbac25c25428

Pith citing papers

No inbound Pith citation observations are available.