Paper Citation Record · LEDGER

BICompFL: Stochastic Federated Learning with Bi-Directional Compression

As of 11 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2502.00206.

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

pith.paper-citation-record.v1
2502.00206 v1

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T19:54:41.688032Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+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

42 of 42 outbound references displayed

verified exact2
verified fuzzy29
unresolved11
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 768df459-a206-4ef4-91ba-d6f34ce29326 · outbound

This paper cites Nested Dithered Quantization for Communication Reduction in Distributed Training.

BICompFL: Stochastic Federated Learning with Bi-Directional Compression Nested Dithered Quantization for Communication Reduction in Distributed Training

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-08-09T19:54:41.900896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation bbbbf099-919c-4f76-8dd7-f6eb6a346417 · outbound

This paper cites QSGD : Communication-efficient SGD via gradient quantization and encoding.

BICompFL: Stochastic Federated Learning with Bi-Directional Compression QSGD : Communication-efficient SGD via gradient quantization and encoding

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:54:42.338757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation c0544a38-da4b-4933-876a-86df72b4880f · outbound

This paper cites Federated Learning With Quantized Global Model Updates.

BICompFL: Stochastic Federated Learning with Bi-Directional Compression Federated Learning With Quantized Global Model Updates

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-09T19:54:41.534388Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7eedc403-1290-4b6a-8395-c447b44200e7 · outbound

This paper cites The sample size required in importance sampling.

BICompFL: Stochastic Federated Learning with Bi-Directional Compression The sample size required in importance sampling

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:54:42.326498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation e591b6f1-2103-41dd-905c-0a5e1eb3bf8c · outbound

This paper cites Communication-Efficient Distributed Learning with Local Immediate Error Compensation.

BICompFL: Stochastic Federated Learning with Bi-Directional Compression Communication-Efficient Distributed Learning with Local Immediate Error Compensation

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-08-09T19:54:41.873974Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 4b20f330-b052-41d9-a8f2-527845e7351a · outbound

This paper cites Elements of information theory.

BICompFL: Stochastic Federated Learning with Bi-Directional Compression Elements of information theory

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:54:42.307945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 1744da45-9161-4912-9f98-9a5d7a5643b0 · outbound

This paper cites DoCoFL : Downlink compression for cross-device federated learning.

BICompFL: Stochastic Federated Learning with Bi-Directional Compression DoCoFL : Downlink compression for cross-device federated learning

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:54:42.290468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 5c4da31c-cee0-48a7-90e6-46be2e9fb03d · outbound

This paper cites The lottery ticket hypothesis: Finding sparse, trainable neural networks.

BICompFL: Stochastic Federated Learning with Bi-Directional Compression The lottery ticket hypothesis: Finding sparse, trainable neural networks

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-09T19:54:41.557577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9438079b-ffd7-40ba-923f-591e66a144ac · outbound

This paper cites vqSGD : Vector quantized stochastic gradient descent.

BICompFL: Stochastic Federated Learning with Bi-Directional Compression vqSGD : Vector quantized stochastic gradient descent

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:54:42.261319Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation ddc12b13-deed-43bf-a068-eebd9bbbfc0b · outbound

This paper cites EF21-P and friends: Improved theoretical communication complexity for distributed optimization with bidirectional compression.

BICompFL: Stochastic Federated Learning with Bi-Directional Compression EF21-P and friends: Improved theoretical communication complexity for distributed optimization with bidirectional compression

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:54:42.247352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d642548d-837f-453f-8cae-b46953b186fd · outbound

This paper cites Improving the Worst-Case Bidirectional Communication Complexity for Nonconvex Distributed Optimization under Function Similarity.

BICompFL: Stochastic Federated Learning with Bi-Directional Compression Improving the Worst-Case Bidirectional Communication Complexity for Nonconvex Distributed Optimization under Function Similarity

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-09T19:54:41.570533Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1197d661-33d5-4340-8e74-75aed0018dbb · outbound

This paper cites Minimal random code learning: Getting bits back from compressed model parameters.

BICompFL: Stochastic Federated Learning with Bi-Directional Compression Minimal random code learning: Getting bits back from compressed model parameters

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:54:42.234124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation c8eb371a-1159-43f6-9484-d9a5d40b5d50 · outbound

This paper cites Natural compression for distributed deep learning.

BICompFL: Stochastic Federated Learning with Bi-Directional Compression Natural compression for distributed deep learning

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:54:42.221432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation c1421abc-9761-4978-a8dc-cf534f98849c · outbound

This paper cites Lower bounds and nearly optimal algorithms in distributed learning with communication compression.

BICompFL: Stochastic Federated Learning with Bi-Directional Compression Lower bounds and nearly optimal algorithms in distributed learning with communication compression

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:54:42.207805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation dbca338a-e874-4d10-9f08-8b671357e528 · outbound

This paper cites Sparse random networks for communication-efficient federated learning.

BICompFL: Stochastic Federated Learning with Bi-Directional Compression Sparse random networks for communication-efficient federated learning

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:54:42.193740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 3d83b14e-be02-437e-8b1f-63d83bd34f47 · outbound

This paper cites Adaptive compression in federated learning via side information.

BICompFL: Stochastic Federated Learning with Bi-Directional Compression Adaptive compression in federated learning via side information

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:54:42.177996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 3a3cb79c-e132-4227-bf0e-1a5454dd274d · outbound

This paper cites Error feedback fixes SignSGD and other gradient compression schemes.

BICompFL: Stochastic Federated Learning with Bi-Directional Compression Error feedback fixes SignSGD and other gradient compression schemes

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:54:42.163882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation edad39fd-e353-4b65-9a5f-ac233568b08d · outbound

This paper cites Adam: A method for stochastic optimization.

BICompFL: Stochastic Federated Learning with Bi-Directional Compression Adam: A method for stochastic optimization

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-09T19:54:41.593996Z

Source-reported events for the cited work

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Observation 40288b40-a1c6-4297-b25c-300e14b04928 · outbound

This paper cites Lecun, L.

BICompFL: Stochastic Federated Learning with Bi-Directional Compression Lecun, L

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-09T19:54:41.597375Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a0d13c6c-7aaa-45d2-99f7-0960ee97c418 · outbound

This paper cites Communication-Efficient Learning of Deep Networks from Decentralized Data.

BICompFL: Stochastic Federated Learning with Bi-Directional Compression Communication-Efficient Learning of Deep Networks from Decentralized Data

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:54:42.136283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 3f2e247e-b4ff-40a3-b8e9-d6907decc848 · outbound

This paper cites Bidirectional compression in heterogeneous settings for distributed or federated learning with partial participation: tight convergence guarantees.

BICompFL: Stochastic Federated Learning with Bi-Directional Compression Bidirectional compression in heterogeneous settings for distributed or federated learning with partial participation: tight convergence guarantees

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-09T19:54:41.604681Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5609cb75-25e5-4179-8e30-b573419491b1 · outbound

This paper cites Preserved central model for faster bidirectional compression in distributed settings.

BICompFL: Stochastic Federated Learning with Bi-Directional Compression Preserved central model for faster bidirectional compression in distributed settings

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:54:42.124185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 5d15b3da-97d1-4827-8e3e-dac0f17246d3 · outbound

This paper cites What's hidden in a randomly weighted neural network? In IEEE/CVF conference on computer vision and pattern recognition, pp.\ 11893--11902, 2020.

BICompFL: Stochastic Federated Learning with Bi-Directional Compression What's hidden in a randomly weighted neural network? In IEEE/CVF conference on computer vision and pattern recognition, pp.\ 11893--11902, 2020

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:54:42.110706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 305c1acf-06ae-4e86-bd4e-e1a8382940ff · outbound

This paper cites Ef21: A new, simpler, theoretically better, and practically faster error feedback.

BICompFL: Stochastic Federated Learning with Bi-Directional Compression Ef21: A new, simpler, theoretically better, and practically faster error feedback

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:54:42.096697Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation c9c3d054-2705-4f05-8da5-e0a8708a2630 · outbound

This paper cites 1-bit stochastic gradient descent and its application to data-parallel distributed training of speech DNNs.

BICompFL: Stochastic Federated Learning with Bi-Directional Compression 1-bit stochastic gradient descent and its application to data-parallel distributed training of speech DNNs

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:54:42.084260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 6daea999-c4c3-49d8-a233-e43fc25bc246 · outbound

This paper cites A distributed synchronous SGD algorithm with global top-k sparsification for low bandwidth networks.

BICompFL: Stochastic Federated Learning with Bi-Directional Compression A distributed synchronous SGD algorithm with global top-k sparsification for low bandwidth networks

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:54:42.072635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation ad57469a-3441-448d-90fe-a7ec5795a9fc · outbound

This paper cites Importance sampling: Applications in communications and detection.

BICompFL: Stochastic Federated Learning with Bi-Directional Compression Importance sampling: Applications in communications and detection

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:54:42.060812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 90fa7a00-b238-42e0-a83e-151e7e478d68 · outbound

This paper cites Sparsified SGD with memory.

BICompFL: Stochastic Federated Learning with Bi-Directional Compression Sparsified SGD with memory

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:54:42.048638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 5973b717-b063-4588-b39c-0eb13fd9a874 · outbound

This paper cites Doublesqueeze: Parallel stochastic gradient descent with double-pass error-compensated compression.

BICompFL: Stochastic Federated Learning with Bi-Directional Compression Doublesqueeze: Parallel stochastic gradient descent with double-pass error-compensated compression

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:54:42.038213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 194fa0e1-b08d-4a3a-8510-20524fb40901 · outbound

This paper cites DP - REC : Private & communication-efficient federated learning, 2022.

BICompFL: Stochastic Federated Learning with Bi-Directional Compression DP - REC : Private & communication-efficient federated learning, 2022

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:54:42.026587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation bc4e7ecd-bf57-4652-9ce9-f7f9b54647c3 · outbound

This paper cites 2Direction: theoretically faster distributed training with bidirectional communication compression.

BICompFL: Stochastic Federated Learning with Bi-Directional Compression 2Direction: theoretically faster distributed training with bidirectional communication compression

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:54:42.014188Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d62d2772-81c6-478e-ad22-220571b9d692 · outbound

This paper cites QLSD: quantised langevin stochastic dynamics for bayesian federated learning.

BICompFL: Stochastic Federated Learning with Bi-Directional Compression QLSD: quantised langevin stochastic dynamics for bayesian federated learning

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:54:42.000723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 89cce0e1-7dc3-47ab-a84a-5768325f172d · outbound

This paper cites Gradient sparsification for communication-efficient distributed optimization.

BICompFL: Stochastic Federated Learning with Bi-Directional Compression Gradient sparsification for communication-efficient distributed optimization

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-09T19:54:41.652442Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3a44b7c4-1df1-429a-aa2f-42bc71a9c06a · outbound

This paper cites Multi-armed bandits with self-information rewards.

BICompFL: Stochastic Federated Learning with Bi-Directional Compression Multi-armed bandits with self-information rewards

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:54:41.977716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 9180f107-4964-42f2-a330-3ee6e4d22e9f · outbound

This paper cites A survey on federated learning: challenges and applications.

BICompFL: Stochastic Federated Learning with Bi-Directional Compression A survey on federated learning: challenges and applications

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-09T19:54:41.659830Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d22ba350-2a1a-47de-8d5e-75edd641c414 · outbound

This paper cites TernGrad : Ternary gradients to reduce communication in distributed deep learning.

BICompFL: Stochastic Federated Learning with Bi-Directional Compression TernGrad : Ternary gradients to reduce communication in distributed deep learning

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:54:41.958484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 5662cd5f-1937-4186-a87f-236f7c198526 · outbound

This paper cites Cser: Communication-efficient sgd with error reset.

BICompFL: Stochastic Federated Learning with Bi-Directional Compression Cser: Communication-efficient sgd with error reset

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:54:41.944787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 0a7a07b8-690f-4cc1-b1b2-722a7c2000b8 · outbound

This paper cites A survey on federated learning.

BICompFL: Stochastic Federated Learning with Bi-Directional Compression A survey on federated learning

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:54:41.934256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 34985e4d-e2a7-42e7-a58b-594356912909 · outbound

This paper cites Communication-efficient distributed blockwise momentum SGD with error-feedback.

BICompFL: Stochastic Federated Learning with Bi-Directional Compression Communication-efficient distributed blockwise momentum SGD with error-feedback

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:54:41.924237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 22c68df7-9592-445c-84bd-66b5758b4926 · outbound

This paper cites @esa (Ref.

BICompFL: Stochastic Federated Learning with Bi-Directional Compression @esa (Ref

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-09T19:54:41.679052Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f0abb1d8-6c9c-498c-ac14-47320f2148bc · outbound

This paper cites an unresolved cited work.

BICompFL: Stochastic Federated Learning with Bi-Directional Compression Unresolved cited work

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-09T19:54:41.683927Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cdc28e84-3747-4859-ba53-63dfce5dd274 · outbound

This paper cites an unresolved cited work.

BICompFL: Stochastic Federated Learning with Bi-Directional Compression Unresolved cited work

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-09T19:54:41.688032Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.