Paper Citation Record · LEDGER

Interaction-Aware Gaussian Weighting for Clustered Federated Learning

As of 13 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 0 inbound Pith citation observations for arXiv:2502.03340.

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

pith.paper-citation-record.v1
2502.03340 v2

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T05:10:22.639430Z

measured 17 of 17 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 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

17 of 17 outbound references displayed

verified exact0
verified fuzzy9
unresolved8
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b6252915-7f93-408d-a715-70ae3aaa472f · outbound

This paper cites The observed value for the random variable is given by ωt k = 1/S PS s=1 rt,s k , which is sampled from a distribution centered on µk.

Interaction-Aware Gaussian Weighting for Clustered Federated Learning The observed value for the random variable is given by ωt k = 1/S PS s=1 rt,s k , which is sampled from a distribution centered on µk

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:10:23.114280Z

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.

Observation 6af1c172-a971-42f8-960e-6b6eeaee0817 · outbound

This paper cites Privacy of FedGWC In the framework of FedGWC, clients are required to send only the empirical loss vectors lt,s k to the server (Cho et al., 2022).

Interaction-Aware Gaussian Weighting for Clustered Federated Learning Privacy of FedGWC In the framework of FedGWC, clients are required to send only the empirical loss vectors lt,s k to the server (Cho et al., 2022)

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:10:22.944638Z

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.

Observation 41c3b642-a41e-42d7-8d18-0dc982c53a48 · outbound

This paper cites We present the balanced accuracy for FedGWC on the Cifar10, Cifar100, and Femnist datasets for β ∈ {0.1, 0.5, 1.0, 2.0, 4.0}.

Interaction-Aware Gaussian Weighting for Clustered Federated Learning We present the balanced accuracy for FedGWC on the Cifar10, Cifar100, and Femnist datasets for β ∈ {0.1, 0.5, 1.0, 2.0, 4.0}

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:10:22.822753Z

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.

Observation f74b47b5-d94f-48a5-afb1-c2c43841c06e · outbound

This paper cites H., Qi, H., and Brown, M.

Interaction-Aware Gaussian Weighting for Clustered Federated Learning H., Qi, H., and Brown, M

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:10:23.165032Z

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.

Observation 448d89b3-c61a-47cd-9603-a202aa1bf12f · outbound

This paper cites Federated Learning with Non-IID Data.

Interaction-Aware Gaussian Weighting for Clustered Federated Learning Federated Learning with Non-IID Data

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-09T05:10:22.330890Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 631f4d4a-9001-4926-9dcc-0bdd49e9f94c · outbound

This paper cites (21) If we iterate backward until P 0 kj, we obtain the following update P t+1 kj = (1 − α)t+1P 0 kj + tX τ =0 α(1 − α)τ ωt−τ k.

Interaction-Aware Gaussian Weighting for Clustered Federated Learning (21) If we iterate backward until P 0 kj, we obtain the following update P t+1 kj = (1 − α)t+1P 0 kj + tX τ =0 α(1 − α)τ ωt−τ k

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:10:23.000496Z

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.

Observation c586dcb1-7f33-480c-965d-76488335fe9f · outbound

This paper cites For Landmarks and iNaturalist, we always refer to the Landmark-Users-160K and iNaturalist-Users-120K partition, respectively.

Interaction-Aware Gaussian Weighting for Clustered Federated Learning For Landmarks and iNaturalist, we always refer to the Landmark-Users-160K and iNaturalist-Users-120K partition, respectively

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:10:22.927531Z

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.

Observation 3d7ee46a-a251-40e0-8fc2-bd178d6c733c · outbound

This paper cites an unresolved cited work.

Interaction-Aware Gaussian Weighting for Clustered Federated Learning Unresolved cited work

Reference 15

Resolution: unresolved; raw_fallback, observed 2026-08-09T05:10:22.910193Z

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.

Observation 11456223-e32c-4586-9b8e-86c2b3cef67b · outbound

This paper cites It utilizes the Rand Index score (Rand, 1971), where a value close to 1 represents a perfect match between clustering and labels.

Interaction-Aware Gaussian Weighting for Clustered Federated Learning It utilizes the Rand Index score (Rand, 1971), where a value close to 1 represents a perfect match between clustering and labels

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:10:22.780752Z

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.

Observation 949c4b7c-945e-4181-93d7-6f5bbb66c910 · outbound

This paper cites Mime: Mimicking Centralized Stochastic Algorithms in Federated Learning.

Interaction-Aware Gaussian Weighting for Clustered Federated Learning Mime: Mimicking Centralized Stochastic Algorithms in Federated Learning

Reference 1942

Resolution: unresolved; no resolver link, observed 2026-08-09T05:10:22.195022Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f608378d-326a-437e-8073-ce56e10117bf · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

Interaction-Aware Gaussian Weighting for Clustered Federated Learning Imagenet: A large-scale hierarchical image database

Reference 1979

Resolution: unresolved; no resolver link, observed 2026-08-09T05:10:22.179058Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 23cbcc7f-b55e-42e3-82c2-6a2cb75e9409 · outbound

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

Interaction-Aware Gaussian Weighting for Clustered Federated Learning FedMD: Heterogenous Federated Learning via Model Distillation

Reference 1998

Resolution: unresolved; no resolver link, observed 2026-08-09T05:10:22.233362Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 92e5ab3f-e0ee-4ccb-9cc2-36b6113cb80f · outbound

This paper cites Fedgroup: Efficient federated learning via decom- posed similarity-based clustering.

Interaction-Aware Gaussian Weighting for Clustered Federated Learning Fedgroup: Efficient federated learning via decom- posed similarity-based clustering

Reference 2009

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:10:23.181234Z

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.

Observation 4f8ac666-be62-4685-8ffe-61f7f50e320a · outbound

This paper cites Federated learning with autotuned communication-efficient secure aggregation.

Interaction-Aware Gaussian Weighting for Clustered Federated Learning Federated learning with autotuned communication-efficient secure aggregation

Reference 2016

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:10:23.208268Z

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.

Observation b956c1d8-c80b-4af5-ac7f-0a76da09f7e7 · outbound

This paper cites FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping.

Interaction-Aware Gaussian Weighting for Clustered Federated Learning FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-09T05:10:22.035691Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 036326aa-78c6-431b-adfd-c26c1f3f73c5 · outbound

This paper cites Practical Secure Aggregation for Federated Learning on User-Held Data.

Interaction-Aware Gaussian Weighting for Clustered Federated Learning Practical Secure Aggregation for Federated Learning on User-Held Data

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-09T05:10:21.907179Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f7bdfed2-e5ba-4360-bc90-9bb073363463 · outbound

This paper cites LEAF: A Benchmark for Federated Settings.

Interaction-Aware Gaussian Weighting for Clustered Federated Learning LEAF: A Benchmark for Federated Settings

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-09T05:10:21.985127Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.