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Paper Citation Record · LEDGER

FedJigsaw: Multi-Agent Collaborative Model Reassembly for Decentralized Heterogeneous Federated Learning

As of 18 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2608.01861.

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

pith.paper-citation-record.v1
2608.01861 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T19:27:40.495197Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

34 of 34 outbound references displayed

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  • verified fuzzy0
  • unresolved34
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4f821ee9-2ad5-4211-a2e6-6c068a3a08b1 · outbound

This paper cites Federated Learning in Mobile Edge Networks: A Comprehensive Survey , year=.

FedJigsaw: Multi-Agent Collaborative Model Reassembly for Decentralized Heterogeneous Federated Learning Federated Learning in Mobile Edge Networks: A Comprehensive Survey , year=

Reference 1

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source=arxiv_source observed=2026-08-04T19:27:40.340896Z digest=sha256:ea19ccf64de34b0880faba112da549d1044b5a1d837ac3785f0fa319cb9cc2aa

Observation e5c997f7-cff5-42ec-ac4d-12f854ac0fd8 · outbound

This paper cites Artificial intelligence and statistics , pages=.

FedJigsaw: Multi-Agent Collaborative Model Reassembly for Decentralized Heterogeneous Federated Learning Artificial intelligence and statistics , pages=

Reference 2

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source=arxiv_source observed=2026-08-04T19:27:40.345521Z digest=sha256:ac9185f57d0bc9254ef36bf31014d5adac7c2ac5220195acc93e87e87a532f0c

Observation afb206bc-44a0-4e2a-bfa1-8d33556f373e · outbound

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

FedJigsaw: Multi-Agent Collaborative Model Reassembly for Decentralized Heterogeneous Federated Learning The Eleventh International Conference on Learning Representations , year=

Reference 3

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no resolver link, observed 2026-08-04T19:27:40.351431Z

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source=arxiv_source observed=2026-08-04T19:27:40.351431Z digest=sha256:84ac8c91c5a94e8d319e3ed48acbd5d081e5827a97d3061a49ddf1b705215fb3

Observation 5c23ab95-c8fc-4db7-a7f3-1a0baef92f6f · outbound

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

FedJigsaw: Multi-Agent Collaborative Model Reassembly for Decentralized Heterogeneous Federated Learning Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , pages=

Reference 4

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no resolver link, observed 2026-08-04T19:27:40.355892Z

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source=arxiv_source observed=2026-08-04T19:27:40.355892Z digest=sha256:2f831c63b79e3912c3678fdac096b407ae581da3e5b098ce8bb360bf4fce0030

Observation 622e1173-c76b-48ac-a14a-9c4f39aac994 · outbound

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

FedJigsaw: Multi-Agent Collaborative Model Reassembly for Decentralized Heterogeneous Federated Learning Advances in neural information processing systems , volume=

Reference 5

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no resolver link, observed 2026-08-04T19:27:40.367699Z

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source=arxiv_source observed=2026-08-04T19:27:40.367699Z digest=sha256:3285d3d74245ab9dd198e1a8a88872b300cae374716a3653aafc2c030cacf4bb

Observation 0d0fa0a9-632d-4577-aaf5-01e10dd1b2f0 · outbound

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

FedJigsaw: Multi-Agent Collaborative Model Reassembly for Decentralized Heterogeneous Federated Learning International Conference on Machine Learning , pages=

Reference 6

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no resolver link, observed 2026-08-04T19:27:40.372519Z

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source=arxiv_source observed=2026-08-04T19:27:40.372519Z digest=sha256:027c353b39d73d59431fb3125515ca747739aa50bb2b767be0cf2a783bee6c43

Observation e742d0bd-f5a3-4d81-a592-b17579b88ee7 · outbound

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

FedJigsaw: Multi-Agent Collaborative Model Reassembly for Decentralized Heterogeneous Federated Learning Advances in neural information processing systems , volume=

Reference 7

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no resolver link, observed 2026-08-04T19:27:40.377443Z

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source=arxiv_source observed=2026-08-04T19:27:40.377443Z digest=sha256:230f5769d8d085755c0da626248ba9a4608cc32011bb93056d3ed4f91674a40b

Observation 6f587773-8b0e-46c5-b0bb-38afce7c5686 · outbound

This paper cites 33rd International Joint Conference on Artificial Intelligence, IJCAI 2024 , pages=.

FedJigsaw: Multi-Agent Collaborative Model Reassembly for Decentralized Heterogeneous Federated Learning 33rd International Joint Conference on Artificial Intelligence, IJCAI 2024 , pages=

Reference 8

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source=arxiv_source observed=2026-08-04T19:27:40.381953Z digest=sha256:4f766cca3ef06af25a229f7157669a5f547e7b14c8fd44b327ee4105bf77eaef

Observation 13aaa271-23c0-405b-b99d-a436643ace69 · outbound

This paper cites Proceedings of the 2023 SIAM International Conference on Data Mining (SDM) , pages=.

FedJigsaw: Multi-Agent Collaborative Model Reassembly for Decentralized Heterogeneous Federated Learning Proceedings of the 2023 SIAM International Conference on Data Mining (SDM) , pages=

Reference 9

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no resolver link, observed 2026-08-04T19:27:40.386126Z

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source=arxiv_source observed=2026-08-04T19:27:40.386126Z digest=sha256:9fae37a0a8e5858c238a5c70716fe4839bcfb1002528cb96b82cbb3ac5898572

Observation 636847bc-27ac-47ef-a1c6-bdcceb49fc18 · outbound

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

FedJigsaw: Multi-Agent Collaborative Model Reassembly for Decentralized Heterogeneous Federated Learning International conference on machine learning , pages=

Reference 10

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no resolver link, observed 2026-08-04T19:27:40.390324Z

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source=arxiv_source observed=2026-08-04T19:27:40.390324Z digest=sha256:aea46ab9d4d74dab2a6f5de385612d33482cae8f87446e64b93c067ffd5b79c5

Observation 56191a60-9b36-468e-9806-c9545f46935b · outbound

This paper cites Proceedings of the AAAI conference on artificial intelligence , volume=.

FedJigsaw: Multi-Agent Collaborative Model Reassembly for Decentralized Heterogeneous Federated Learning Proceedings of the AAAI conference on artificial intelligence , volume=

Reference 11

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source=arxiv_source observed=2026-08-04T19:27:40.394938Z digest=sha256:9602e45e660634e514a933bd873355c703bf7ca502aef96d65b155dad2ce7eaa

Observation 4b0b61db-b259-4148-8950-c017caf55de1 · outbound

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

FedJigsaw: Multi-Agent Collaborative Model Reassembly for Decentralized Heterogeneous Federated Learning Advances in Neural Information Processing Systems , volume=

Reference 12

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no resolver link, observed 2026-08-04T19:27:40.399417Z

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source=arxiv_source observed=2026-08-04T19:27:40.399417Z digest=sha256:2bd9b42070c107316a745749f73220958c54fa75b0027546eb0f4897f0214768

Observation d5b1fda6-4524-4af8-bb42-578787c67f9e · outbound

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

FedJigsaw: Multi-Agent Collaborative Model Reassembly for Decentralized Heterogeneous Federated Learning Advances in neural information processing systems , volume=

Reference 13

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no resolver link, observed 2026-08-04T19:27:40.403840Z

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source=arxiv_source observed=2026-08-04T19:27:40.403840Z digest=sha256:18d21ded6e55e69b093b085aaa8cc236d752e69af2e472db75f618b7f580968f

Observation 1c5d94b1-a5e4-4c83-9aa8-f6e991fd898f · outbound

This paper cites FedMD: Heterogenous Federated Learning via Model Distillation.

FedJigsaw: Multi-Agent Collaborative Model Reassembly for Decentralized Heterogeneous Federated Learning FedMD: Heterogenous Federated Learning via Model Distillation

Reference 14

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source=arxiv_source observed=2026-08-04T19:27:40.407990Z digest=sha256:33900be73d4597d55e0dda8868aec1fa5b4afe753c6e055970cb889ceca2f816

Observation f3e1a132-f7a5-49db-a006-3f39371ab520 · outbound

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

FedJigsaw: Multi-Agent Collaborative Model Reassembly for Decentralized Heterogeneous Federated Learning Advances in Neural Information Processing Systems , volume=

Reference 15

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no resolver link, observed 2026-08-04T19:27:40.413395Z

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source=arxiv_source observed=2026-08-04T19:27:40.413395Z digest=sha256:08853ddc1bb2805e7340069634f41ab470fa97e48a419bd70b33fc0d8909f08c

Observation c367ee14-2ab9-4be8-94aa-179a091c15a5 · outbound

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

FedJigsaw: Multi-Agent Collaborative Model Reassembly for Decentralized Heterogeneous Federated Learning Advances in Neural Information Processing Systems , volume=

Reference 16

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no resolver link, observed 2026-08-04T19:27:40.417219Z

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source=arxiv_source observed=2026-08-04T19:27:40.417219Z digest=sha256:549e4123fbb8b9f95b0454b29b6cb2b0114177dd8209d05e1e4fa66542a11136

Observation 943d2cac-12be-4724-b48e-9b6371e10bcf · outbound

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

FedJigsaw: Multi-Agent Collaborative Model Reassembly for Decentralized Heterogeneous Federated Learning IEEE transactions on knowledge and data engineering , volume=

Reference 17

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no resolver link, observed 2026-08-04T19:27:40.421156Z

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source=arxiv_source observed=2026-08-04T19:27:40.421156Z digest=sha256:0ab74f654d3164014624177fe49880cf7ac237c5aa6a600de6081e8a66089e5f

Observation 6d53517b-8b32-4a6c-9adf-4752b6b4c8cf · outbound

This paper cites Pacific-Asia Conference on Knowledge Discovery and Data Mining , pages=.

FedJigsaw: Multi-Agent Collaborative Model Reassembly for Decentralized Heterogeneous Federated Learning Pacific-Asia Conference on Knowledge Discovery and Data Mining , pages=

Reference 18

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source=arxiv_source observed=2026-08-04T19:27:40.425127Z digest=sha256:0d15543ce97131028079200e05bd1e77d0580ba9eb72a97e882c9f471dec7624

Observation 3604926b-97fd-493a-b384-5aaac1fed430 · outbound

This paper cites IEEE Internet of Things Journal , volume=.

FedJigsaw: Multi-Agent Collaborative Model Reassembly for Decentralized Heterogeneous Federated Learning IEEE Internet of Things Journal , volume=

Reference 19

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source=arxiv_source observed=2026-08-04T19:27:40.429554Z digest=sha256:5c896e6601a943733f8cc17e760818270e029432261578b6a06b0d240706340a

Observation 773a12f8-b9d7-41cb-806e-a7271e936dcd · outbound

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

FedJigsaw: Multi-Agent Collaborative Model Reassembly for Decentralized Heterogeneous Federated Learning Advances in neural information processing systems , volume=

Reference 20

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no resolver link, observed 2026-08-04T19:27:40.433742Z

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source=arxiv_source observed=2026-08-04T19:27:40.433742Z digest=sha256:f9c10bf974ccccbaeb61eec83e351a3ae8b6ad1d84b58181484117b52496f857

Observation ac300495-3f14-48f4-896b-a7c7d991d414 · outbound

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

FedJigsaw: Multi-Agent Collaborative Model Reassembly for Decentralized Heterogeneous Federated Learning Advances in Neural Information Processing Systems , volume=

Reference 21

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no resolver link, observed 2026-08-04T19:27:40.437920Z

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source=arxiv_source observed=2026-08-04T19:27:40.437920Z digest=sha256:d532c4a8bc269b03dad58746900cf6d64efbebf01cda0269f10185215d50d605

Observation ee60007d-e1d7-4e3f-80d8-dd589e087466 · outbound

This paper cites 9th International Conference on Learning Representations, ICLR 2021 , year=.

FedJigsaw: Multi-Agent Collaborative Model Reassembly for Decentralized Heterogeneous Federated Learning 9th International Conference on Learning Representations, ICLR 2021 , year=

Reference 22

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source=arxiv_source observed=2026-08-04T19:27:40.442087Z digest=sha256:b1735ca87aeb0fdbdb6186aa202958aed47753c9a21b33c9b0f5e11778d90bfe

Observation c7da9e34-c323-449d-a617-a58d1051e3df · outbound

This paper cites IEEE wireless communications letters , volume=.

FedJigsaw: Multi-Agent Collaborative Model Reassembly for Decentralized Heterogeneous Federated Learning IEEE wireless communications letters , volume=

Reference 23

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source=arxiv_source observed=2026-08-04T19:27:40.445940Z digest=sha256:cde34eadf33f52c6f7c72c3082ee7699186a2d65881a394a464a9269720c92ef

Observation 9a6fa946-e2cb-4bb5-a75c-c7a76d6e000e · outbound

This paper cites IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems , volume=.

FedJigsaw: Multi-Agent Collaborative Model Reassembly for Decentralized Heterogeneous Federated Learning IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems , volume=

Reference 24

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source=arxiv_source observed=2026-08-04T19:27:40.449985Z digest=sha256:a4df28bc793814b13d2f091544c937f34b75c95365099a60a8c5093b5861acf2

Observation 80deeba5-b892-45a0-a79f-3db3a97f2df0 · outbound

This paper cites FedShapleX: Shapley Value Driven Context-Aware Model-Heterogeneous Federated Learning , year=.

FedJigsaw: Multi-Agent Collaborative Model Reassembly for Decentralized Heterogeneous Federated Learning FedShapleX: Shapley Value Driven Context-Aware Model-Heterogeneous Federated Learning , year=

Reference 25

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source=arxiv_source observed=2026-08-04T19:27:40.455473Z digest=sha256:10d8712c9c597568a6b5c14c9a6e7f3037af4945886037fe4c19ff8e617ab8b9

Observation 442af116-77ae-4314-ba93-685304953782 · outbound

This paper cites Towards Non-I.I.D. and Invisible Data with FedNAS: Federated Deep Learning via Neural Architecture Search.

FedJigsaw: Multi-Agent Collaborative Model Reassembly for Decentralized Heterogeneous Federated Learning Towards Non-I.I.D. and Invisible Data with FedNAS: Federated Deep Learning via Neural Architecture Search

Reference 26

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source=arxiv_source observed=2026-08-04T19:27:40.460009Z digest=sha256:95b01c20a8c1a986efe6fd791274b39c663d9ed05a742694b4eda7f5a6541751

Observation 055ba8aa-bdf4-4441-a9f1-859e222677a7 · outbound

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

FedJigsaw: Multi-Agent Collaborative Model Reassembly for Decentralized Heterogeneous Federated Learning Advances in Neural Information Processing Systems , volume=

Reference 27

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no resolver link, observed 2026-08-04T19:27:40.464952Z

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source=arxiv_source observed=2026-08-04T19:27:40.464952Z digest=sha256:b2573d56621b356920d819932db3d395dcaec60b587045d96284e1639db76f8f

Observation 1952157b-8f81-4b7f-81c9-895304d9758d · outbound

This paper cites Proceedings of the AAAI Conference on Artificial Intelligence , volume=.

FedJigsaw: Multi-Agent Collaborative Model Reassembly for Decentralized Heterogeneous Federated Learning Proceedings of the AAAI Conference on Artificial Intelligence , volume=

Reference 28

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no resolver link, observed 2026-08-04T19:27:40.469039Z

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source=arxiv_source observed=2026-08-04T19:27:40.469039Z digest=sha256:b048e952a2ca8c7060c56305c614a160078a34df98f99f81577b58dd4b8750ac

Observation 393ecc26-b063-461c-9315-cef55f2fcef5 · outbound

This paper cites IEEE Transactions on Mobile Computing , volume=.

FedJigsaw: Multi-Agent Collaborative Model Reassembly for Decentralized Heterogeneous Federated Learning IEEE Transactions on Mobile Computing , volume=

Reference 29

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no resolver link, observed 2026-08-04T19:27:40.473676Z

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source=arxiv_source observed=2026-08-04T19:27:40.473676Z digest=sha256:6bb084bf57c109d1b5b15dfd310ceec01d2dcf97dbbb7130c425a5ad71a40d94

Observation 5f1e6180-a958-49ac-b231-d6ba61eb7713 · outbound

This paper cites Proceedings of the AAAI Conference on Artificial Intelligence , volume=.

FedJigsaw: Multi-Agent Collaborative Model Reassembly for Decentralized Heterogeneous Federated Learning Proceedings of the AAAI Conference on Artificial Intelligence , volume=

Reference 30

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source=arxiv_source observed=2026-08-04T19:27:40.477811Z digest=sha256:1138053f7b89fe1c971a199a8a69081d755941b95afecfb6f6784ddfbf06c184

Observation 8b34dd6c-6adc-4ef8-801c-257a22ee4866 · outbound

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

FedJigsaw: Multi-Agent Collaborative Model Reassembly for Decentralized Heterogeneous Federated Learning International conference on machine learning , pages=

Reference 31

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no resolver link, observed 2026-08-04T19:27:40.482167Z

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source=arxiv_source observed=2026-08-04T19:27:40.482167Z digest=sha256:74a000f7f6b850b0e14d42dce96c4eb37c6289af97cb7be24858fccb95ee58df

Observation 1805c6e2-c09a-481c-8901-c7cf30d3ebe0 · outbound

This paper cites Journal of Artificial Intelligence Research , volume=.

FedJigsaw: Multi-Agent Collaborative Model Reassembly for Decentralized Heterogeneous Federated Learning Journal of Artificial Intelligence Research , volume=

Reference 32

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source=arxiv_source observed=2026-08-04T19:27:40.487143Z digest=sha256:586b84a6abb8fb3a59c0d83831fffa111bae63dd9dda746815fee675843c01b7

Observation 25d98145-e2f1-4641-bd1f-8e56a09b54c8 · outbound

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

FedJigsaw: Multi-Agent Collaborative Model Reassembly for Decentralized Heterogeneous Federated Learning Advances in neural information processing systems , volume=

Reference 33

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source=arxiv_source observed=2026-08-04T19:27:40.491235Z digest=sha256:fd78c3779f59654a979c36a0154059710b07c0fba568072012713e72fe7d4f0d

Observation 599ca8ca-6aaa-4aeb-8a58-eb74596b8897 · outbound

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

FedJigsaw: Multi-Agent Collaborative Model Reassembly for Decentralized Heterogeneous Federated Learning Advances in neural information processing systems , volume=

Reference 34

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no resolver link, observed 2026-08-04T19:27:40.495197Z

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source=arxiv_source observed=2026-08-04T19:27:40.495197Z digest=sha256:9a14627a790451e9e5eb7d6db4f085c27963a0694b496c80ca600b62377762d9

Pith citing papers

No inbound Pith citation observations are available.