Paper Citation Record · LEDGER

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning

As of 8 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2511.18887.

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

pith.paper-citation-record.v1
2511.18887 v1

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T20:43:49.328055Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

45 of 45 outbound references displayed

verified exact0
verified fuzzy0
unresolved45
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0417cfa9-d423-4e14-8f43-711a7a9a9d9d · outbound

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

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning Communication-efficient learning of deep networks from decentralized data,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-03T20:43:44.374646Z

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Observation fceae81c-2227-4c5c-bd50-4f4aae013315 · outbound

This paper cites Recent advances on federated learning for cybersecurity and cybersecurity for federated learning for internet of things,.

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning Recent advances on federated learning for cybersecurity and cybersecurity for federated learning for internet of things,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-03T20:43:44.486133Z

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Observation e2bd7224-de24-495b-a266-005a889587d3 · outbound

This paper cites Federated learning for medical applications: A taxonomy, current trends, challenges, and future research directions,.

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning Federated learning for medical applications: A taxonomy, current trends, challenges, and future research directions,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-03T20:43:44.685013Z

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Observation 51bd1c13-9af5-4f20-8aee-8d3d9252c59b · outbound

This paper cites Federated learning: Challenges, methods, and future directions,.

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning Federated learning: Challenges, methods, and future directions,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-03T20:43:44.869811Z

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Observation 51392eb9-fb05-4325-bb86-f2910aceaa5d · outbound

This paper cites Communication-efficient randomized algorithm for multi-kernel online federated learning,.

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning Communication-efficient randomized algorithm for multi-kernel online federated learning,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-03T20:43:44.996769Z

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Observation dca4812d-7a28-4aa2-bd9b-aa83f54b65d2 · outbound

This paper cites Tighter regret analysis and optimization of online federated learning,.

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning Tighter regret analysis and optimization of online federated learning,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-03T20:43:45.104962Z

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Observation ea73b345-aa87-46c6-a16a-d32439f9cda4 · outbound

This paper cites Federated learning in mobile edge networks: A comprehensive survey,.

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning Federated learning in mobile edge networks: A comprehensive survey,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-03T20:43:45.249636Z

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Observation 9580b159-ac79-46e4-b0f2-24b72258c680 · outbound

This paper cites A survey on vertical federated learning: From theory to applications,.

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning A survey on vertical federated learning: From theory to applications,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-03T20:43:45.329946Z

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Unavailable: canonical work link unavailable.

Observation 73dbebfa-c880-4abc-80bd-17ba02ee5bd7 · outbound

This paper cites Privacy and robustness in federated learning: Attacks and defenses,.

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning Privacy and robustness in federated learning: Attacks and defenses,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-03T20:43:45.498575Z

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Observation 57e0a025-ea3b-49e3-8bd0-4050e52ce111 · outbound

This paper cites A survey on federated learning: The journey from centralized machine learning to privacy-preserving edge learning,.

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning A survey on federated learning: The journey from centralized machine learning to privacy-preserving edge learning,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-03T20:43:45.631555Z

Source-reported events for the cited work

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Observation cbd4dadb-d590-49d8-965e-256f2e592010 · outbound

This paper cites Federated learning: A survey on enabling technologies, challenges, and open issues,.

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning Federated learning: A survey on enabling technologies, challenges, and open issues,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-03T20:43:45.819642Z

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Observation 4c7a14c5-c096-451e-8dcb-1b8df12089d5 · outbound

This paper cites Advances and open problems in federated learning,.

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning Advances and open problems in federated learning,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T20:43:45.982442Z

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Observation 6f465cac-d6e6-4a7d-aec2-acc6f8e1df3f · outbound

This paper cites Deep leakage from gradients,.

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning Deep leakage from gradients,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-03T20:43:46.129679Z

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Observation 281ceabd-8952-4a62-9f8a-60fa28d9e240 · outbound

This paper cites Deep models under the gan: information leakage from collaborative deep learning,.

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning Deep models under the gan: information leakage from collaborative deep learning,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-03T20:43:46.327215Z

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Observation 03c0679c-9c27-4079-947e-6acb06d2e7a1 · outbound

This paper cites Inverting gradients-how easy is it to break privacy in federated learning?.

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning Inverting gradients-how easy is it to break privacy in federated learning?

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-03T20:43:46.480570Z

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Observation f85663ba-42e6-45a0-8934-cb727a97a9b4 · outbound

This paper cites Comprehensive privacy analysis of deep learning: Passive and active white-box inference attacks against centralized and federated learning,.

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning Comprehensive privacy analysis of deep learning: Passive and active white-box inference attacks against centralized and federated learning,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-03T20:43:46.651291Z

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Observation 4c80e8ab-b9b9-49ec-9902-a886a017008d · outbound

This paper cites Gradient leakage attack resilient deep learning,.

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning Gradient leakage attack resilient deep learning,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-03T20:43:46.878611Z

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Observation fd7b0726-c69d-4d03-9e0a-68226238d5f4 · outbound

This paper cites Practical secure aggregation for privacy-preserving machine learning,.

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning Practical secure aggregation for privacy-preserving machine learning,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-03T20:43:46.998751Z

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Observation 16a9a411-d678-4d1b-9e8d-50620f69d7b5 · outbound

This paper cites Lightsecagg: a lightweight and versatile design for secure aggregation in federated learning,.

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning Lightsecagg: a lightweight and versatile design for secure aggregation in federated learning,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-03T20:43:47.180114Z

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Observation b429132f-41fd-424b-abe9-0f005e39cb2d · outbound

This paper cites A hybrid approach to privacy-preserving federated learning,.

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning A hybrid approach to privacy-preserving federated learning,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-03T20:43:47.255980Z

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Observation 9fdf02de-f235-438f-a662-28efc6544fb4 · outbound

This paper cites DP-SIGNSGD: When Efficiency Meets Privacy and Robustness.

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning DP-SIGNSGD: When Efficiency Meets Privacy and Robustness

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-03T20:43:47.433198Z

Source-reported events for the cited work

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Observation 410126d8-4986-4340-8a3f-14bd146e15b4 · outbound

This paper cites Homomorphic encryption for arithmetic of approximate numbers,.

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning Homomorphic encryption for arithmetic of approximate numbers,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-03T20:43:47.575564Z

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Unavailable: canonical work link unavailable.

Observation 0ff37f22-3155-42ab-80a6-4f9458524fa8 · outbound

This paper cites Privacy preserving machine learning with ho- momorphic encryption and federated learning,.

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning Privacy preserving machine learning with ho- momorphic encryption and federated learning,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-03T20:43:47.802732Z

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Unavailable: canonical work link unavailable.

Observation fc1b2aa7-89e2-400b-9758-e001ec546427 · outbound

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

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning 1-bit stochastic gradient descent and its application to data-parallel distributed training of speech dnns,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-03T20:43:47.972951Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c34276eb-633f-47b9-b953-9bace60242bc · outbound

This paper cites signSGD: Compressed optimisation for non-convex problems,.

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning signSGD: Compressed optimisation for non-convex problems,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-03T20:43:48.091270Z

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Observation f796369f-2a1f-4544-b87b-333543c0f956 · outbound

This paper cites signSGD with Majority Vote is Communication Efficient And Fault Tolerant.

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning signSGD with Majority Vote is Communication Efficient And Fault Tolerant

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-03T20:43:48.174999Z

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Observation 1024740f-7b4a-4438-9c59-c6271af14a94 · outbound

This paper cites Sparse-SignSGD with Majority Vote for Communication-Efficient Distributed Learning.

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning Sparse-SignSGD with Majority Vote for Communication-Efficient Distributed Learning

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-03T20:43:48.243482Z

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Observation c84441f1-d7ca-4d83-94ce-609ee6121613 · outbound

This paper cites Sign-based gradient descent with heterogeneous data: Convergence and byzantine resilience,.

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning Sign-based gradient descent with heterogeneous data: Convergence and byzantine resilience,

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-03T20:43:48.290614Z

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Observation bdacf33d-6a31-4da7-aff1-c916e737d67d · outbound

This paper cites FedLSC: Improving communi- cation efficiency and robustness in federated learning with stragglers and adversaries,.

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning FedLSC: Improving communi- cation efficiency and robustness in federated learning with stragglers and adversaries,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-03T20:43:48.321792Z

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Observation d8ce120e-57c7-4e30-9adb-a691440e0334 · outbound

This paper cites Differentially private secure multi- party computation for federated learning in financial applications,.

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning Differentially private secure multi- party computation for federated learning in financial applications,

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-03T20:43:48.384143Z

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Unavailable: canonical work link unavailable.

Observation 4e821e36-ed09-46f7-9df4-2f5527e8e519 · outbound

This paper cites Batchcrypt: Efficient homomorphic encryption for cross-silo federated learning,.

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning Batchcrypt: Efficient homomorphic encryption for cross-silo federated learning,

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-03T20:43:48.441294Z

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Observation ba045ad0-7859-466b-adc9-d590f34f6693 · outbound

This paper cites FLASHE: Additively Symmetric Homomorphic Encryption for Cross-Silo Federated Learning.

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning FLASHE: Additively Symmetric Homomorphic Encryption for Cross-Silo Federated Learning

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-03T20:43:48.510371Z

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Unavailable: canonical work link unavailable.

Observation aa8b50b2-4835-458f-8e0f-f5fd2d351545 · outbound

This paper cites Privacy-preserving federated learning based on multi-key homomorphic encryption,.

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning Privacy-preserving federated learning based on multi-key homomorphic encryption,

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-03T20:43:48.598867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7fdaf487-f2c8-4663-a1d6-a12052a81afc · outbound

This paper cites Fully homomorphic encryption using ideal lattices,.

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning Fully homomorphic encryption using ideal lattices,

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-03T20:43:48.631933Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d8cb3e79-bff4-46c8-96df-c083bb3cbdee · outbound

This paper cites Ahsecagg and tskg: Lightweight secure aggregation for federated learning without compromise,.

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning Ahsecagg and tskg: Lightweight secure aggregation for federated learning without compromise,

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-03T20:43:48.684718Z

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Observation af2a540f-a189-4cf2-8242-11faf3f46e7b · outbound

This paper cites Correlations of the Riemann zeta function.

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning Correlations of the Riemann zeta function

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-03T20:43:48.716908Z

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Unavailable: canonical work link unavailable.

Observation 0bfb0b3a-e407-421a-b58b-76c438c11cf1 · outbound

This paper cites Pqsf: Post-quantum secure privacy-preserving federated learning,.

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning Pqsf: Post-quantum secure privacy-preserving federated learning,

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-03T20:43:48.768934Z

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Unavailable: canonical work link unavailable.

Observation a76332af-bbcb-43c8-8861-f223e6521f80 · outbound

This paper cites Secure and flexible privacy- preserving federated learning based on multi-key fully homomorphic encryption,.

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning Secure and flexible privacy- preserving federated learning based on multi-key fully homomorphic encryption,

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-03T20:43:48.869283Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2c957ace-c769-432f-a906-cd24e58cfc41 · outbound

This paper cites Efficient multiparty protocols using circuit randomization,.

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning Efficient multiparty protocols using circuit randomization,

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-03T20:43:48.979018Z

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Unavailable: canonical work link unavailable.

Observation afdc805a-bb5f-49f7-85b7-16b368f8c487 · outbound

This paper cites Scalable and unconditionally secure multiparty computation,.

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning Scalable and unconditionally secure multiparty computation,

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-03T20:43:49.037317Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 83a61e37-bd26-41b6-8019-e18179dd8933 · outbound

This paper cites ATLAS: efficient and scalable mpc in the honest majority setting,.

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning ATLAS: efficient and scalable mpc in the honest majority setting,

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-03T20:43:49.174861Z

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Unavailable: canonical work link unavailable.

Observation 321c9b37-2cb3-42a8-aff3-8b1eb89d0978 · outbound

This paper cites Applications of fermat’s little theorem in cryptography,.

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning Applications of fermat’s little theorem in cryptography,

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-03T20:43:49.200424Z

Source-reported events for the cited work

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Observation 1763b515-3711-48da-a37b-3cffa527dbec · outbound

This paper cites Gradient-based learning applied to document recognition,.

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning Gradient-based learning applied to document recognition,

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-03T20:43:49.250021Z

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Unavailable: canonical work link unavailable.

Observation 73003c41-3d33-4ec7-a716-c9691c5b80a0 · outbound

This paper cites Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms.

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-03T20:43:49.257602Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa3559c6-f53c-4db4-892d-fde9541311d8 · outbound

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

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning Learning multiple layers of features from tiny images,

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-03T20:43:49.328055Z

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Pith citing papers

No inbound Pith citation observations are available.