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Paper Citation Record · LEDGER

Advances and Open Problems in Federated Learning

As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 25 inbound Pith citation observations for arXiv:1912.04977.

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

pith.paper-citation-record.v1
1912.04977 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00

measured 25 of 25 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T18:23:49.814485Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-07-10T11:37:03.437032Z

Reference resolution

0 of 0 outbound references displayed

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  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation b66c28b9-d96a-42ae-85f7-33fed6dfb427 · inbound

Adaptive Federated Optimization cites this paper.

Adaptive Federated Optimization Advances and Open Problems in Federated Learning

Reference 219

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verified exact
arxiv_id, observed 2026-05-21T10:30:58.819880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=arxiv_source observed=2026-05-21T10:30:58.601351Z digest=sha256:f35a3dbf82c5fda345c929c08ff5674891f40a9450bbba835cfd9a8ad0f53689

Observation 333ac724-7d05-4c00-8189-ca7b1ff88e0a · inbound

BoBa: Boosting Backdoor Detection through Data Distribution Inference in Federated Learning cites this paper.

BoBa: Boosting Backdoor Detection through Data Distribution Inference in Federated Learning Advances and Open Problems in Federated Learning

Reference 3

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verified exact
arxiv_id, observed 2026-05-23T23:13:37.066433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-23T23:09:32.656257Z digest=sha256:6da8a74cef1c213f7207f3d79bfd78e13a03d60644837ff12380829cf392487c

Observation c37b39c6-4ff5-4918-8900-e80f50455327 · inbound

Compass: SLO-aware Query Planner for Compound AI Serving at Scale cites this paper.

Compass: SLO-aware Query Planner for Compound AI Serving at Scale Advances and Open Problems in Federated Learning

Reference 46

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arxiv_id, observed 2026-05-22T19:15:03.467974Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-22T19:14:58.225504Z digest=sha256:01e20d7956f4b300ac69048a6c6d8dd4d16ea0fcee8508aed5ae0ec829a0a605

Observation d92b4b91-594c-4a29-9f3b-34c97149fd6b · inbound

A Blueprint for AI-Driven Software Quality: Integrating LLMs with Established Standards cites this paper.

A Blueprint for AI-Driven Software Quality: Integrating LLMs with Established Standards Advances and Open Problems in Federated Learning

Reference 257

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verified exact
arxiv_id, observed 2026-05-22T13:46:37.107011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-22T13:45:28.789452Z digest=sha256:c64fa5c073677c9d0f9d5a34773873148cddebc0f9e4f7dce6406e4a267aff16

Observation 3505ea63-e03b-47c3-af5a-ab4b2a1e8ffc · inbound

LADSG: Label-Anonymized Distillation and Similar Gradient Substitution for Label Privacy in Vertical Federated Learning cites this paper.

LADSG: Label-Anonymized Distillation and Similar Gradient Substitution for Label Privacy in Vertical Federated Learning Advances and Open Problems in Federated Learning

Reference 21

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metadata mismatch
arxiv_id, observed 2026-05-19T11:17:15.426979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-19T11:14:54.323233Z digest=sha256:b61ff1de24feb0ae5254122b9fab5e031f0a400e48544103092585f0f7ef5048

Observation 496eb9e5-97ed-48a9-8c26-d93db54da78f · inbound

FedRP: A Communication-Efficient Approach for Differentially Private Federated Learning Using Random Projection cites this paper.

FedRP: A Communication-Efficient Approach for Differentially Private Federated Learning Using Random Projection Advances and Open Problems in Federated Learning

Reference 36

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unresolved
no resolver link, observed 2026-08-04T18:23:49.814485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T18:23:49.814485Z digest=sha256:2e5a7c8efb600303389c555fee37afdee24e07dfa3d8e290171e789a1b92e643

Observation 4ddc88da-7b8d-406b-8cfb-ad2d6d735851 · inbound

Federated Learning for Surgical Vision in Appendicitis Classification: Results of the FedSurg EndoVis 2024 Challenge cites this paper.

Federated Learning for Surgical Vision in Appendicitis Classification: Results of the FedSurg EndoVis 2024 Challenge Advances and Open Problems in Federated Learning

Reference 13

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verified exact
arxiv_id, observed 2026-05-18T10:26:14.416517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-18T10:22:32.253706Z digest=sha256:45700946db27491e14ae2f889be6945c3cacba915e898c66fb6445e1db8e300a

Observation d2bb0fc2-75f0-4f4e-9a05-0c9d9039c57b · inbound

FLARE: Adaptive Multi-Dimensional Reputation for Robust Client Reliability in Federated Learning cites this paper.

FLARE: Adaptive Multi-Dimensional Reputation for Robust Client Reliability in Federated Learning Advances and Open Problems in Federated Learning

Reference 8

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metadata mismatch
arxiv_id, observed 2026-05-17T20:10:10.996165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-17T20:08:21.578954Z digest=sha256:8eab07660c69607676e32040c40f5bcf6eafb97c4ba70c501c5900a891827c90

Observation cc1af5a1-dd5b-4ddb-8072-579182827b76 · inbound

SuperSFL: Resource-Heterogeneous Federated Split Learning with Weight-Sharing Super-Networks cites this paper.

SuperSFL: Resource-Heterogeneous Federated Split Learning with Weight-Sharing Super-Networks Advances and Open Problems in Federated Learning

Reference 3

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unresolved
no resolver link, observed 2026-08-03T12:42:39.098318Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T12:42:39.098318Z digest=sha256:b0fa22c318554f1883237d59a47163d86453942294475e08326ca629d857909e

Observation 92b88797-64c0-4d7d-9082-7bcd580ee2e7 · inbound

Understanding Communication Backends in Cross-Silo Federated Learning cites this paper.

Understanding Communication Backends in Cross-Silo Federated Learning Advances and Open Problems in Federated Learning

Reference 1

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verified exact
arxiv_id, observed 2026-05-11T11:16:08.363167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-10T15:03:32.069261Z digest=sha256:26e7cd185342472f416ea22d7b28f8c9dceb2e24d80200b1019271237ff31670

Observation c1e23736-5dda-40c3-9680-8f67cda1fb9a · inbound

Choose Wisely and Privately: Proactive Client Selection for Fair and Efficient Federated Learning cites this paper.

Choose Wisely and Privately: Proactive Client Selection for Fair and Efficient Federated Learning Advances and Open Problems in Federated Learning

Reference 2

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verified exact
arxiv_id, observed 2026-05-21T06:13:59.718510Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-21T06:09:45.435627Z digest=sha256:bd54b3442ddc2e0b429677ebf47ace3d45cb84413cee9d78e3018dd85e44def3

Observation e3a534f3-821e-425b-8caa-00aaf6fbbde3 · inbound

Choose Wisely and Privately: Proactive Client Selection for Fair and Efficient Federated Learning cites this paper.

Choose Wisely and Privately: Proactive Client Selection for Fair and Efficient Federated Learning Advances and Open Problems in Federated Learning

Reference 2

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verified exact
arxiv_id, observed 2026-05-22T10:11:22.938436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-22T10:10:13.980897Z digest=sha256:6c856ea2829af014738aa677c5192165cb69e2965e2562afaac6af0688dd03f7

Observation 20443fe2-56a3-44b7-b3f8-ce013655e5d7 · inbound

A Tight Theory of Error Feedback Algorithms in Distributed Optimization cites this paper.

A Tight Theory of Error Feedback Algorithms in Distributed Optimization Advances and Open Problems in Federated Learning

Reference 22

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metadata mismatch
arxiv_id, observed 2026-06-29T00:12:50.692984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=arxiv_source observed=2026-06-28T23:07:05.700294Z digest=sha256:5f09173669dc6b51d82e98b8f2513977b1a36997e29f3aa8e43a37b94960d3b3

Observation 71b2e125-9aaa-4513-94e0-a7bf2988ada6 · inbound

Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning cites this paper.

Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning Advances and Open Problems in Federated Learning

Reference 16

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verified exact
arxiv_id, observed 2026-07-02T22:07:25.962385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-06-27T19:17:23.711817Z digest=sha256:8ede97baa612a642ec6cb1cde19969efcf8b187dfae58d17bdb3c939754718f9

Observation 91cb5e76-b1b2-4f79-9a97-508f9bba7517 · inbound

Adaptive Joint Compression and Synchronisation in Federated Split Learning for IoT Rainfall Prediction cites this paper.

Adaptive Joint Compression and Synchronisation in Federated Split Learning for IoT Rainfall Prediction Advances and Open Problems in Federated Learning

Reference 6

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verified exact
arxiv_id, observed 2026-07-04T17:09:58.638633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-06-25T23:57:17.666605Z digest=sha256:9f96a0db0e4c8810bd4c8a98c42f843c76a093faf8ff58c970c8a9d8d8bf8d93

Observation 1ee5b844-a797-4c5e-8d65-4c7e8e4277d6 · inbound

Tuning-Free Efficient Estimation for Multi-Source Data via Covariance-Aware Shrinkage cites this paper.

Tuning-Free Efficient Estimation for Multi-Source Data via Covariance-Aware Shrinkage Advances and Open Problems in Federated Learning

Reference 130

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metadata mismatch
arxiv_id, observed 2026-06-30T16:44:56.412004Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=arxiv_source observed=2026-06-30T04:41:41.370083Z digest=sha256:4fcc9b36325287f4e3866fe346a9b75025ea7138ff8588d1885ce05323e74e60

Observation 65d4e80a-77bc-4526-95ea-066b912a61f6 · inbound

Expected Gain-based Escalation in Vertical Federated Learning cites this paper.

Expected Gain-based Escalation in Vertical Federated Learning Advances and Open Problems in Federated Learning

Reference 2

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metadata mismatch
arxiv_id, observed 2026-07-01T09:55:40.134729Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-07-01T06:09:52.967421Z digest=sha256:0df52fd95549f323e23465b07cd643f0fc0019386206d2c97b5388b7f3ae2ac3

Observation e3262e47-603d-4881-8e50-a07075651a0e · inbound

TallyTrain: Communication-Efficient Federated Distillation cites this paper.

TallyTrain: Communication-Efficient Federated Distillation Advances and Open Problems in Federated Learning

Reference 26

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metadata mismatch
arxiv_id, observed 2026-07-02T19:47:18.819598Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=arxiv_source observed=2026-07-02T19:44:47.733008Z digest=sha256:2b59cb937276faaa58dc277abd0bbf802089bd88be736c069f952756579fbdf7

Observation 3c134799-fe5a-4da6-8fa3-c727e96c4d5b · inbound

Learning Adaptive Coarse Spaces Using Transferable Neural Network Models for Linear and Nonlinear Overlapping Domain Decomposition Methods cites this paper.

Learning Adaptive Coarse Spaces Using Transferable Neural Network Models for Linear and Nonlinear Overlapping Domain Decomposition Methods Advances and Open Problems in Federated Learning

Reference 86

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local_arxiv, observed 2026-07-08T11:44:51.104973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=arxiv_source observed=2026-07-08T11:43:37.974923Z digest=sha256:7abc3ce31ed359bcab4e49cccbda393c9710c6dfe09cdc7c6d6d0631903d9a37

Observation ecf38250-a076-4ab4-8977-cc3cf3d32bb6 · inbound

MLQENABLER: Enabling Secure Machine Learning Queries over Encrypted Database in Cloud Computing cites this paper.

MLQENABLER: Enabling Secure Machine Learning Queries over Encrypted Database in Cloud Computing Advances and Open Problems in Federated Learning

Reference 13

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verified exact
local_arxiv, observed 2026-07-10T11:37:03.438481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-07-10T11:29:45.184868Z digest=sha256:e09f1df774478ab626425ce08a13e559515fabb557a865503174944f58c4e373

Observation 0344b03b-56c0-45ae-9f90-c0f295747a33 · inbound

What's in a Smoothness Constant? Tighter Rates for Local SGD with Bounded Second-order Heterogeneity cites this paper.

What's in a Smoothness Constant? Tighter Rates for Local SGD with Bounded Second-order Heterogeneity Advances and Open Problems in Federated Learning

Reference 8

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no resolver link, observed 2026-08-02T01:23:30.669742Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T01:23:30.669742Z digest=sha256:5764cb1c428573a20eedbac4b3e688330a3c5688a3580572293f1fc2e0a861bc

Observation c5d13690-d0b2-40ed-a64e-b99203c6ce5a · inbound

Joint Channel Estimation and Dynamics-Aware Grouping for Time-Varying RIS-Assisted OTA Federated Learning cites this paper.

Joint Channel Estimation and Dynamics-Aware Grouping for Time-Varying RIS-Assisted OTA Federated Learning Advances and Open Problems in Federated Learning

Reference 6

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no resolver link, observed 2026-08-01T18:53:31.815069Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T18:53:31.815069Z digest=sha256:42ddd42ff49315226539bb09da41b4fbcd001f91b06b7cdd5932814da5d9bd0a

Observation 6adbe5db-3536-4405-817e-9072e99cdf61 · inbound

Federated Lightweight Fine-Tuning cites this paper.

Federated Lightweight Fine-Tuning Advances and Open Problems in Federated Learning

Reference 9

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no resolver link, observed 2026-08-01T17:36:04.174872Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T17:36:04.174872Z digest=sha256:368218ee099a53b19ad200db88edb3bd6c6d1d32e1078dba29077c3899e796f5

Observation 01a2163d-c99c-4b94-959d-8d3c43340ee5 · inbound

Sarus: Privacy-Preserving Multi-Vendor Perception Fusion via Homomorphic Encryption cites this paper.

Sarus: Privacy-Preserving Multi-Vendor Perception Fusion via Homomorphic Encryption Advances and Open Problems in Federated Learning

Reference 37

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unresolved
no resolver link, observed 2026-08-01T13:23:27.828578Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T13:23:27.828578Z digest=sha256:457a2c07be95d7a75ce5b601d30809d8ad45aac258c0cb3b15ae7c66db972079

Observation eaf64394-9dc0-4f46-8b80-34bf23064be2 · inbound

Autonomous Collaborative Learning Among an Ensemble of Tsetlin Machines with Consensus-Based Inference cites this paper.

Autonomous Collaborative Learning Among an Ensemble of Tsetlin Machines with Consensus-Based Inference Advances and Open Problems in Federated Learning

Reference 34

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no resolver link, observed 2026-08-01T10:45:24.323993Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T10:45:24.323993Z digest=sha256:59e872dd83d7ef6169ddbfd58d7acd58bd7f5dc862e077de0ef30ea9a0fb1f15