Pith. sign in

Paper Citation Record · LEDGER

Communication Efficiency in Federated Learning: Achievements and Challenges

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2107.10996.

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

pith.paper-citation-record.v1
2107.10996 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T11:51:37.883574Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T13:49:51.287324Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

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 e7a1e631-550a-4943-9c13-8180d0eaf453 · inbound

Knowledge Distillation in Federated Learning: a Survey on Long Lasting Challenges and New Solutions cites this paper.

Knowledge Distillation in Federated Learning: a Survey on Long Lasting Challenges and New Solutions Communication Efficiency in Federated Learning: Achievements and Challenges

Reference 128

Resolution
verified exact
arxiv_id, observed 2026-05-23T23:48:39.370598Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-23T23:47:28.874336Z digest=sha256:cd05cbab4bb9652b7af3cf133047f6a538710265dbe88d3f80636df4bf47062f

Observation 674582e2-6901-48cb-b80f-caeedfad47d0 · inbound

Adaptive Client Selection with Personalization for Communication Efficient Federated Learning cites this paper.

Adaptive Client Selection with Personalization for Communication Efficient Federated Learning Communication Efficiency in Federated Learning: Achievements and Challenges

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-12T11:51:37.883574Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T11:51:37.883574Z digest=sha256:75e486e3e509a0da38abe950af66ebd1acc564671da10df3956e374c451afbe3

Observation 0586f9c2-f22a-4b27-8dd6-c1a071787a65 · inbound

A Robust Federated Learning Framework for Undependable Devices at Scale cites this paper.

A Robust Federated Learning Framework for Undependable Devices at Scale Communication Efficiency in Federated Learning: Achievements and Challenges

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-10T23:45:18.348131Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:45:18.348131Z digest=sha256:81ade57947a41f2655c126aa9dc2e5c9ee1f6870ba84642076af199916803389

Observation a3d60137-eecc-47a7-8df5-10768d7be04f · inbound

Encoded Spatial Attribute in Multi-Tier Federated Learning cites this paper.

Encoded Spatial Attribute in Multi-Tier Federated Learning Communication Efficiency in Federated Learning: Achievements and Challenges

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-10T21:11:44.403257Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:11:44.403257Z digest=sha256:de26f753b144632025a839b4fb933bd29c9fb6f093aeaebeb3472d0b49007436

Observation d6847343-df6c-4af3-9277-da985ba3f05c · inbound

Privacy-Preserving Personalized Federated Prompt Learning for Multimodal Large Language Models cites this paper.

Privacy-Preserving Personalized Federated Prompt Learning for Multimodal Large Language Models Communication Efficiency in Federated Learning: Achievements and Challenges

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-10T15:35:30.502442Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T15:35:30.502442Z digest=sha256:d4c29555d39c1b1923568bee80dbcbe23073100b617836784ada70cc32dc0297

Observation ec8c23bb-d06c-4e30-997d-31cb07aea371 · inbound

Enhancing Model Privacy in Federated Learning with Random Masking and Quantization cites this paper.

Enhancing Model Privacy in Federated Learning with Random Masking and Quantization Communication Efficiency in Federated Learning: Achievements and Challenges

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-05T16:10:53.354510Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:10:53.354510Z digest=sha256:18c5703a839170c04904a5f77bd7d63f6d08d49bb3cf272ea926bb67c7584fa7

Observation 3648656d-137b-4372-8319-ec4cb13cfb22 · inbound

Self-Play Enhancement via Advantage-Weighted Refinement in Online Federated LLM Fine-Tuning with Real-Time Feedback cites this paper.

Self-Play Enhancement via Advantage-Weighted Refinement in Online Federated LLM Fine-Tuning with Real-Time Feedback Communication Efficiency in Federated Learning: Achievements and Challenges

Reference 32

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T03:50:54.505846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-11T02:15:57.763495Z digest=sha256:7ad7e384214caf53a4d29e47efcd00e39bbe412d57fead1119b5c04baeb2b80d

Observation f370cf35-b3e0-47cb-a8f9-3fd6632388bf · inbound

COSMOS: Model-Agnostic Personalized Federated Learning with Clustered Server Models and Pseudo-Label-Only Communication cites this paper.

COSMOS: Model-Agnostic Personalized Federated Learning with Clustered Server Models and Pseudo-Label-Only Communication Communication Efficiency in Federated Learning: Achievements and Challenges

Reference 26

Resolution
verified exact
arxiv_id, observed 2026-05-13T06:07:22.291927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-13T06:05:02.954856Z digest=sha256:2dfc808ae775ec9f18b6703083d2a39382d27044a01f6f38f9f85c2b5ef24ae0

Observation 7ef54a6d-ae06-473b-b395-e7dcff8f2741 · inbound

COSMOS: Model-Agnostic Personalized Federated Learning with Clustered Server Models and Pseudo-Label-Only Communication cites this paper.

COSMOS: Model-Agnostic Personalized Federated Learning with Clustered Server Models and Pseudo-Label-Only Communication Communication Efficiency in Federated Learning: Achievements and Challenges

Reference 26

Resolution
verified exact
arxiv_id, observed 2026-07-01T14:05:46.260639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-06-30T22:21:47.617478Z digest=sha256:aeebf8802f3a4055b688e4480df4729193e43ce9b0e0edb4c75f9677dd317258

Observation 8a35840f-4b54-4d5f-8c5f-da128f69a6f1 · inbound

Quantization in Federated Learning: Methods, Challenges and Future Directions cites this paper.

Quantization in Federated Learning: Methods, Challenges and Future Directions Communication Efficiency in Federated Learning: Achievements and Challenges

Reference 107

Resolution
verified exact
arxiv_id, observed 2026-07-04T13:49:51.289064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-06-26T04:56:12.424439Z digest=sha256:fee22fdf62dab26638f4692b07cee11f7bdf089ebede208471a2bd1995292052