Paper Citation Record · LEDGER

FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions

As of 19 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 1 inbound Pith citation observation for arXiv:2508.04470.

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

pith.paper-citation-record.v1
2508.04470 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T00:03:29.800883Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-27T13:40:35.795292Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T04:47:37.956236Z

Reference resolution

40 of 40 outbound references displayed

verified exact0
verified fuzzy36
unresolved4
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a5fe8be6-4e0a-4699-8413-a8866af32816 · outbound

This paper cites FairFed: Improving fairness and efficiency of contribution evaluation in federated learning via cooperative shapley value,.

FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions FairFed: Improving fairness and efficiency of contribution evaluation in federated learning via cooperative shapley value,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:03:38.360834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1b91f719-186c-49a1-be7d-27b1fef03707 · outbound

This paper cites Communication-efficient learning of deep networks from decentralized data,.

FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions Communication-efficient learning of deep networks from decentralized data,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T00:03:26.292086Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cf62e7d5-94a4-4630-9285-acdeaaa661d8 · outbound

This paper cites Federated optimization in heterogeneous networks,.

FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions Federated optimization in heterogeneous networks,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T00:03:26.357013Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e33bc528-bcb8-4931-97d2-92a33a8c900b · outbound

This paper cites Towards personalized federated learning,.

FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions Towards personalized federated learning,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:03:38.002313Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1e6e507e-023e-4173-97f8-1e2acf5382f3 · outbound

This paper cites Ditto: Fair and robust federated learning through personalization,.

FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions Ditto: Fair and robust federated learning through personalization,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:03:37.731358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d5d679a4-4913-44f3-b481-5f3cd9dfd2b3 · outbound

This paper cites FedALA: Adaptive local aggregation for personalized federated learn- ing,.

FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions FedALA: Adaptive local aggregation for personalized federated learn- ing,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:03:37.490000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c76e2a05-e5d3-48bf-af39-a604525edf82 · outbound

This paper cites FedLFP: Communication-efficient personalized federated learning on non-iid data in mobile edge computing environments,.

FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions FedLFP: Communication-efficient personalized federated learning on non-iid data in mobile edge computing environments,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:03:37.237215Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9b3666fb-e2db-4b0e-ab06-75a7c3d23616 · outbound

This paper cites Personalized federated learning with model-contrastive learning for multi-modal user modeling in human-centric metaverse,.

FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions Personalized federated learning with model-contrastive learning for multi-modal user modeling in human-centric metaverse,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:03:36.915788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e07bc8a4-4c09-4a34-b8ef-aa83271757f1 · outbound

This paper cites Multi-level person- alized federated learning on heterogeneous and long-tailed data,.

FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions Multi-level person- alized federated learning on heterogeneous and long-tailed data,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:03:36.570770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation abf207dd-49a6-40a1-a5d0-f0094aaafba1 · outbound

This paper cites Federated learning while providing model as a service: Joint training and inference optimization,.

FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions Federated learning while providing model as a service: Joint training and inference optimization,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:03:36.299774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2c1e7142-28fc-4f37-94cd-00331f7c3d5d · outbound

This paper cites CPDZ: A credibility-aware and privacy-preserving data collection scheme with zero-trust in next-generation crowdsensing networks,.

FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions CPDZ: A credibility-aware and privacy-preserving data collection scheme with zero-trust in next-generation crowdsensing networks,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:03:36.075472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e840d91d-9f7b-4684-9345-e18edbaf1a4b · outbound

This paper cites QLP-DCS: A quality-aware, low-cost, and privacy- preserving data collection service for mobile crowd sensing,.

FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions QLP-DCS: A quality-aware, low-cost, and privacy- preserving data collection service for mobile crowd sensing,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:03:35.834000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8f8619c9-923a-4cf5-9037-99279df9cb78 · outbound

This paper cites RMDF-CV: A reliable multi-source data fusion scheme with cross validation for quality service construction in mobile crowd sensing,.

FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions RMDF-CV: A reliable multi-source data fusion scheme with cross validation for quality service construction in mobile crowd sensing,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:03:35.586885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 77d0d1a7-3dbc-40ee-b6ae-13f12a601150 · outbound

This paper cites Pseudoinverse learning algo- rithm for feedforward neural networks,.

FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions Pseudoinverse learning algo- rithm for feedforward neural networks,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:03:35.356267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation bdec1553-1b17-4b46-90b3-8ae1aed94f51 · outbound

This paper cites GKEAL: Gaussian kernel embedded analytic learning for few-shot class incremental task,.

FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions GKEAL: Gaussian kernel embedded analytic learning for few-shot class incremental task,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:03:35.156718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation fc3f3b9b-897c-433a-9cd3-ac58e1de2258 · outbound

This paper cites ACIL: Analytic class-incremental learning with absolute memorization and privacy protection,.

FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions ACIL: Analytic class-incremental learning with absolute memorization and privacy protection,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:03:34.937716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ae6a9f24-c844-473c-bcf2-df1694fe4efa · outbound

This paper cites A progressive stacking pseudoinverse learning framework via active learning in random sub- spaces,.

FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions A progressive stacking pseudoinverse learning framework via active learning in random sub- spaces,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:03:34.706376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation aec51504-a289-4d8a-a666-e19c634a81b3 · outbound

This paper cites Bayesian pseudoinverse learners: From uncertainty to deterministic learning,.

FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions Bayesian pseudoinverse learners: From uncertainty to deterministic learning,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:03:34.453884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9075756f-232b-4042-ab90-c25ec81fc56b · outbound

This paper cites Universal approximation using radial-basis- function networks,.

FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions Universal approximation using radial-basis- function networks,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:03:34.222402Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 70c0762b-e66f-413a-9127-5eb136b2cb60 · outbound

This paper cites Learning from the kernel and the range space,.

FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions Learning from the kernel and the range space,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:03:34.008326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e0e1ea2b-a9a9-451d-8a20-130cca45e34b · outbound

This paper cites Noniterative deep learning: Incorporating restricted boltzmann machine into multilayer random weight neural networks,.

FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions Noniterative deep learning: Incorporating restricted boltzmann machine into multilayer random weight neural networks,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:03:33.771127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 6e4faa46-c819-422d-ad28-9a5e82053d68 · outbound

This paper cites An analytic formulation of convolutional neural network learning for pattern recognition,.

FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions An analytic formulation of convolutional neural network learning for pattern recognition,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:03:33.544219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 679246ee-f8de-42b9-933e-18ad1ca0054b · outbound

This paper cites Densepilae: a feature reuse pseudoinverse learning algorithm for deep stacked autoencoder,.

FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions Densepilae: a feature reuse pseudoinverse learning algorithm for deep stacked autoencoder,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:03:33.358183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c4ea7005-b330-4371-ac32-2dd7676dca81 · outbound

This paper cites Blockwise recursive moore–penrose inverse for network learning,.

FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions Blockwise recursive moore–penrose inverse for network learning,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:03:33.140795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 34ecb4da-8420-478f-947d-ab56ab6a770e · outbound

This paper cites CALM: A ubiquitous crowdsourced analytic learning mechanism for continual service construction with data privacy preservation,.

FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions CALM: A ubiquitous crowdsourced analytic learning mechanism for continual service construction with data privacy preservation,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:03:32.893767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 262a31d4-2a75-453a-be28-c8549df513c4 · outbound

This paper cites AFL: A single-round analytic approach for federated learing with pre-trained models,.

FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions AFL: A single-round analytic approach for federated learing with pre-trained models,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:03:32.714605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ea68d8b0-0a0f-4c84-a6b3-bd5e9ea052c9 · outbound

This paper cites Locality sensitive sparse encoding for learning world models online,.

FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions Locality sensitive sparse encoding for learning world models online,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:03:32.480177Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 12920f81-539a-4faa-a9b9-de2198ebfbcb · outbound

This paper cites Masked au- toencoders are scalable vision learners,.

FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions Masked au- toencoders are scalable vision learners,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:03:32.271336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1d1ab36c-7b2e-4789-ab83-790af477a4e7 · outbound

This paper cites Where to begin? on the impact of pre-training and initialization in federated learning,.

FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions Where to begin? on the impact of pre-training and initialization in federated learning,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:03:32.027821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e9033b7d-1f19-4699-8bf3-80ec0913a7cb · outbound

This paper cites On the importance and applicability of pre-training for federated learning,.

FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions On the importance and applicability of pre-training for federated learning,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:03:31.815545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 659f6feb-f7f2-46b0-90dc-e64033d8a079 · outbound

This paper cites FedBERT: When federated learning meets pre-training,.

FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions FedBERT: When federated learning meets pre-training,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:03:31.612193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9665840f-1cfc-497e-a2ff-72390593a294 · outbound

This paper cites AugFL: Aug- menting federated learning with pretrained models,.

FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions AugFL: Aug- menting federated learning with pretrained models,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:03:31.436540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ce77ebf3-677a-4504-9adc-ad96c5dd895d · outbound

This paper cites FedDAT: An approach for foundation model finetuning in multi-modal heterogeneous federated learning,.

FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions FedDAT: An approach for foundation model finetuning in multi-modal heterogeneous federated learning,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:03:31.188737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 6b41b684-aded-41bb-852a-e1c2f2779c1e · outbound

This paper cites Learning multiple layers of features from tiny images,.

FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions Learning multiple layers of features from tiny images,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:03:31.003609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 6a7d327b-b9e8-44da-b946-90ddd1a99f23 · outbound

This paper cites The many faces of robustness: A critical analysis of out-of-distribution generalization,.

FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions The many faces of robustness: A critical analysis of out-of-distribution generalization,

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-06T00:03:29.415884Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6cc8d20d-6217-4c9a-bc99-39a04a225a25 · outbound

This paper cites Eliminating domain bias for federated learning in representa- tion space,.

FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions Eliminating domain bias for federated learning in representa- tion space,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:03:30.833929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0a0c64b9-1403-4abf-a70b-ca372ac1f7d6 · outbound

This paper cites FedAS: Bridging inconsistency in personalized federated learning,.

FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions FedAS: Bridging inconsistency in personalized federated learning,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:03:30.634289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2eba1061-6e5b-4dae-b608-f8b119739287 · outbound

This paper cites Federated learning from pre-trained models: A contrastive learning approach,.

FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions Federated learning from pre-trained models: A contrastive learning approach,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:03:30.449841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 829876da-4df7-43fb-bcd8-35b74b20a488 · outbound

This paper cites FedSelect: Personalized federated learning with customized selection of parameters for fine-tuning,.

FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions FedSelect: Personalized federated learning with customized selection of parameters for fine-tuning,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:03:30.247904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ddb5b7ae-4667-404e-acdc-e599fe56936b · outbound

This paper cites an unresolved cited work.

FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions Unresolved cited work

Reference 2008

Resolution: unresolved; raw_fallback, observed 2026-08-06T00:03:30.030354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

Observation 98e11c00-8351-455e-ad39-5a9f3f024033 · inbound

Accurate and Resource-Efficient Federated Continual Learning cites this paper.

Accurate and Resource-Efficient Federated Continual Learning FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions

Reference 58

Resolution: verified exact; arxiv_id, observed 2026-07-03T04:47:37.957769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.