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Paper Citation Record · LEDGER

Strategic Incentivization for Locally Differentially Private Federated Learning

As of 9 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2508.07138.

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

pith.paper-citation-record.v1
2508.07138 v1

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T22:25:20.102168Z

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

44 of 44 outbound references displayed

  • verified exact5
  • verified fuzzy32
  • unresolved7
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 257750c2-8e11-40d1-ac57-edbcca7961f7 · outbound

This paper cites Towards efficient and privacy-preserving federated deep learning,.

Strategic Incentivization for Locally Differentially Private Federated Learning Towards efficient and privacy-preserving federated deep learning,

Reference 1

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raw_fallback, observed 2026-08-05T22:25:20.635561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 15c43a60-173c-4957-99fa-7fc5fc722e4d · outbound

This paper cites Collecting telemetry data privately,.

Strategic Incentivization for Locally Differentially Private Federated Learning Collecting telemetry data privately,

Reference 2

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raw_fallback, observed 2026-08-05T22:25:20.626542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation ebd1b27d-c076-4d21-a4a8-0d9246a1b325 · outbound

This paper cites Motivating Workers in Federated Learning: A Stackelberg Game Perspective.

Strategic Incentivization for Locally Differentially Private Federated Learning Motivating Workers in Federated Learning: A Stackelberg Game Perspective

Reference 3

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no resolver link, observed 2026-08-05T22:25:19.961303Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:25:19.961303Z digest=sha256:5506c054efbf392311f05f1034a4114bf69267f7f9cecb5bf8e8f7e4afb85f73

Observation c74a1fb4-2340-4757-bea6-a8da54e876a7 · outbound

This paper cites A learning-based incentive mechanism for federated learning,.

Strategic Incentivization for Locally Differentially Private Federated Learning A learning-based incentive mechanism for federated learning,

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-05T22:25:20.616307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T22:25:19.965208Z digest=sha256:9bc92edf3e6e7f9f1027dfe478c2705fb6bc5bec8b86725ad97b074b437aef44

Observation de76ac6d-1da4-4a68-bdd5-81f40c408cd8 · outbound

This paper cites Joint Service Pricing and Cooperative Relay Communication for Federated Learning.

Strategic Incentivization for Locally Differentially Private Federated Learning Joint Service Pricing and Cooperative Relay Communication for Federated Learning

Reference 5

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verified exact
local_arxiv, observed 2026-08-05T22:25:20.235826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T22:25:19.968898Z digest=sha256:ea98332d5ba6653b052ede122fd6a742b1ca3f567f2eaae9115cb3eeace400f4

Observation 5cfc1c49-774b-4d0a-be99-9614ff4d8d40 · outbound

This paper cites Fmore: An incentive scheme of multi-dimensional auction for federated learning in mec,.

Strategic Incentivization for Locally Differentially Private Federated Learning Fmore: An incentive scheme of multi-dimensional auction for federated learning in mec,

Reference 6

Resolution
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raw_fallback, observed 2026-08-05T22:25:20.604730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation c7078946-ed7b-4675-8124-d422137e3116 · outbound

This paper cites Toward an Automated Auction Framework for Wireless Federated Learning Services Market.

Strategic Incentivization for Locally Differentially Private Federated Learning Toward an Automated Auction Framework for Wireless Federated Learning Services Market

Reference 7

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verified exact
local_arxiv, observed 2026-08-05T22:25:20.217377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation d65d2bad-ade3-40c1-b79a-9b804f839887 · outbound

This paper cites Auction based incentive design for efficient federated learning in cellular wireless networks,.

Strategic Incentivization for Locally Differentially Private Federated Learning Auction based incentive design for efficient federated learning in cellular wireless networks,

Reference 8

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raw_fallback, observed 2026-08-05T22:25:20.594074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T22:25:19.981772Z digest=sha256:10c4508b82de1a65f9532e8c9460455edfea287d7f36ca534fad47ee3591ac84

Observation 9ac427f4-6126-4379-be5a-62859978ab31 · outbound

This paper cites Incentivized federated learning with local differential privacy using permissioned blockchains,.

Strategic Incentivization for Locally Differentially Private Federated Learning Incentivized federated learning with local differential privacy using permissioned blockchains,

Reference 9

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raw_fallback, observed 2026-08-05T22:25:20.583260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T22:25:19.985769Z digest=sha256:c475df6007e1f89774d1b73342c0eb439aab5299b974f08d6c00ceeced8804f1

Observation 890cce81-9320-4400-b352-7ff54cdde044 · outbound

This paper cites Blockchain based secure federated learning with local differential privacy and incentivization,.

Strategic Incentivization for Locally Differentially Private Federated Learning Blockchain based secure federated learning with local differential privacy and incentivization,

Reference 10

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raw_fallback, observed 2026-08-05T22:25:20.571944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T22:25:19.988779Z digest=sha256:23068ad46313eb9046f9e942644f187faff552795f06f6b6ab5b7c56d26711d5

Observation ba547c24-4511-471c-b99a-fed5c8f0c636 · outbound

This paper cites Incentive mechanism for differentially private federated learning in industrial internet of things,.

Strategic Incentivization for Locally Differentially Private Federated Learning Incentive mechanism for differentially private federated learning in industrial internet of things,

Reference 11

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raw_fallback, observed 2026-08-05T22:25:20.561764Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T22:25:19.991781Z digest=sha256:c436619d7b23c445e9e351a04c92c706fc9c91465797436c26a76f8eeb1a0964

Observation 1fa7d81c-4179-49c0-8966-b6e486902555 · outbound

This paper cites The mnist database of handwritten digit images for machine learning research,.

Strategic Incentivization for Locally Differentially Private Federated Learning The mnist database of handwritten digit images for machine learning research,

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:25:19.995615Z digest=sha256:943db5ecb896534fa5e6f87e62a0387f15d12d10fb133a1a6b743a49b6c437bf

Observation 747e7592-df53-47a3-82e5-c7ff1efea83e · outbound

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

Strategic Incentivization for Locally Differentially Private Federated Learning Learning multiple layers of features from tiny images,

Reference 13

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raw_fallback, observed 2026-08-05T22:25:20.546497Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T22:25:19.998653Z digest=sha256:f06789ce0041a14d44bbe8ba22bc26d8fb42f84c7e6f76b1bbfe208b46446cc6

Observation 7fcb46a1-2490-452c-9e87-47b64a22b21b · outbound

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

Strategic Incentivization for Locally Differentially Private Federated Learning Communication-Efficient Learning of Deep Networks from Decentralized Data

Reference 14

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no resolver link, observed 2026-08-05T22:25:20.001993Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:25:20.001993Z digest=sha256:9d9f570eb65a10f7173b8b03f7ab522063a5473ee5cd08634498a3792cdd40ed

Observation 93369284-8a6b-4a79-ae5d-72ae8ca09848 · outbound

This paper cites What is federated learning?.

Strategic Incentivization for Locally Differentially Private Federated Learning What is federated learning?

Reference 15

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verified fuzzy
raw_fallback, observed 2026-08-05T22:25:20.536615Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T22:25:20.005577Z digest=sha256:169aa96f36cb47629e249c1cf5ec4b575dc9d41023f72c40815cfda95539f168

Observation 1776a2a1-aa74-440d-bbf7-e3b772dfc68f · outbound

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

Strategic Incentivization for Locally Differentially Private Federated Learning Advances and open problems in federated learning,

Reference 16

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raw_fallback, observed 2026-08-05T22:25:20.527600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T22:25:20.008828Z digest=sha256:395d42e4e58ca93e3c33d13ecfa3bbabcd57374486ec012b81c994ccc7e81b2d

Observation 8e6c550c-3176-48b3-a2ca-4b41742bf3c0 · outbound

This paper cites Calibrating noise to sensitivity in private data analysis,.

Strategic Incentivization for Locally Differentially Private Federated Learning Calibrating noise to sensitivity in private data analysis,

Reference 17

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raw_fallback, observed 2026-08-05T22:25:20.518552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T22:25:20.011938Z digest=sha256:437202beedd94862ed664b6100a629b526d7951e40a4ccab0609f9d79efc6f9a

Observation 08ec8079-429d-4c73-8247-c777b10d8a46 · outbound

This paper cites Local Differential Privacy and Its Applications: A Comprehensive Survey.

Strategic Incentivization for Locally Differentially Private Federated Learning Local Differential Privacy and Its Applications: A Comprehensive Survey

Reference 18

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verified exact
local_arxiv, observed 2026-08-05T22:25:20.188710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T22:25:20.015105Z digest=sha256:43b1e7eaf97b833ce72441db4f42fed92b325b5e001f8cd9e40b6a4bfda10c0f

Observation cdca56d0-4672-4e49-92b1-d3c92923a237 · outbound

This paper cites What can we learn privately?.

Strategic Incentivization for Locally Differentially Private Federated Learning What can we learn privately?

Reference 19

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raw_fallback, observed 2026-08-05T22:25:20.509094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T22:25:20.018873Z digest=sha256:425ff5e7e92f228507aa304e2e00f6560b5c9169e0d4fa3bac87baa428b03ef3

Observation b841a8d4-c7f2-4364-9b7b-8920e88cee6c · outbound

This paper cites Differentially private asynchronous federated learning for mobile edge computing in urban informatics,.

Strategic Incentivization for Locally Differentially Private Federated Learning Differentially private asynchronous federated learning for mobile edge computing in urban informatics,

Reference 20

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raw_fallback, observed 2026-08-05T22:25:20.499217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T22:25:20.022833Z digest=sha256:61c0be88cdfea32405108b1652f65158958882b83574535ba050db4da02d14c8

Observation 36c95c36-6a75-48bb-907b-fbf81064355f · outbound

This paper cites Ldp-fed: Federated learning with local differential privacy,.

Strategic Incentivization for Locally Differentially Private Federated Learning Ldp-fed: Federated learning with local differential privacy,

Reference 21

Resolution
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raw_fallback, observed 2026-08-05T22:25:20.488989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T22:25:20.026165Z digest=sha256:8e5e21be8a60d5e997e21a47b53a7d264f219fa7f70d74a99ab652c008452178

Observation 6dba5f0c-f956-46f8-9a05-4071be871935 · outbound

This paper cites Local differential privacy-based federated learning for internet of things,.

Strategic Incentivization for Locally Differentially Private Federated Learning Local differential privacy-based federated learning for internet of things,

Reference 22

Resolution
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raw_fallback, observed 2026-08-05T22:25:20.480042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T22:25:20.029417Z digest=sha256:3b8206cf45a135506317e56c670243fae9d04189f18a1a43531bbc6d3e2ca455

Observation 79a2b1bb-7fd1-4ec9-855a-46ebff3edf05 · outbound

This paper cites LDP-FL: Practical private aggregation in federated learning with local differential privacy,.

Strategic Incentivization for Locally Differentially Private Federated Learning LDP-FL: Practical private aggregation in federated learning with local differential privacy,

Reference 23

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verified fuzzy
raw_fallback, observed 2026-08-05T22:25:20.470906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T22:25:20.032547Z digest=sha256:534cbd30a33f97f9dadeb211ac7dc23495a2a266e3235c52a664c0fcf57396c8

Observation 808d87aa-f5f1-4943-b1bc-626683df1738 · outbound

This paper cites Nisan et al., Algorithmic Game Theory.

Strategic Incentivization for Locally Differentially Private Federated Learning Nisan et al., Algorithmic Game Theory

Reference 24

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raw_fallback, observed 2026-08-05T22:25:20.461395Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T22:25:20.035600Z digest=sha256:ed06662d7a78b19e39d5b25000afc37b241650c25ac6bb27b18f6468befe9f55

Observation 9bd2895b-5799-4efe-91b1-f1646dd72986 · outbound

This paper cites Ldp-fl: Practical private aggregation in federated learning with local differential privacy,.

Strategic Incentivization for Locally Differentially Private Federated Learning Ldp-fl: Practical private aggregation in federated learning with local differential privacy,

Reference 25

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verified fuzzy
raw_fallback, observed 2026-08-05T22:25:20.452022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T22:25:20.038607Z digest=sha256:a37190231b509cd776d36b85a3d56cf882e1b0244bc7a2adb3d7d702fccdccc2

Observation 4088775e-0f6b-4f85-90bb-107c2e7b69f5 · outbound

This paper cites Local differential privacy for federated learning,.

Strategic Incentivization for Locally Differentially Private Federated Learning Local differential privacy for federated learning,

Reference 26

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raw_fallback, observed 2026-08-05T22:25:20.443125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T22:25:20.041832Z digest=sha256:ffa5714daf2a33349227254d094e17c0c9640d304e87f1bc94b3d47942898223

Observation 1c5bcce3-65c0-4037-afd3-6562e16c47f3 · outbound

This paper cites Incentivizing Federated Learning.

Strategic Incentivization for Locally Differentially Private Federated Learning Incentivizing Federated Learning

Reference 27

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no resolver link, observed 2026-08-05T22:25:20.045086Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:25:20.045086Z digest=sha256:25f90209080e922e624070e46be128f9281a85062009cd4e3c92d87be1c2e90a

Observation fb5c8c42-4f1a-4be2-833a-beabc4d7d5a4 · outbound

This paper cites Towards Fair and Privacy-Preserving Federated Deep Models.

Strategic Incentivization for Locally Differentially Private Federated Learning Towards Fair and Privacy-Preserving Federated Deep Models

Reference 28

Resolution
verified exact
local_arxiv, observed 2026-08-05T22:25:20.150822Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T22:25:20.048476Z digest=sha256:72ad015744dfd0c9ef1ee26ce069712819550376597ce219f521caee335960b7

Observation 88c0e9f4-f271-4b4c-98b6-65b93fb5dab8 · outbound

This paper cites Incentive-aware federated learning with training- time model rewards,.

Strategic Incentivization for Locally Differentially Private Federated Learning Incentive-aware federated learning with training- time model rewards,

Reference 29

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verified fuzzy
raw_fallback, observed 2026-08-05T22:25:20.431964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T22:25:20.051884Z digest=sha256:1ee914a20c27002aeadbbe8a5f9d1a5501ca4ce0d9b6d87929525daf116e27ef

Observation ba856bab-5014-4c20-a4ff-95ca34f2cb2b · outbound

This paper cites A sustainable incentive scheme for federated learning,.

Strategic Incentivization for Locally Differentially Private Federated Learning A sustainable incentive scheme for federated learning,

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:25:20.421952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T22:25:20.055442Z digest=sha256:8a7328c77ffaddee4f6cc4df0a6dc11c6bb85e6146c8b9dad25ecfb5cef15ed9

Observation bb203324-5bf6-442b-8446-b87486034988 · outbound

This paper cites A note on stackelberg games,.

Strategic Incentivization for Locally Differentially Private Federated Learning A note on stackelberg games,

Reference 31

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raw_fallback, observed 2026-08-05T22:25:20.411871Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T22:25:20.059923Z digest=sha256:1af7a5a0bc3867ea560de95d5634811a2868281e861bd285647a24f354c5973f

Observation 15c9ad9b-8808-4495-a508-c3641a3b9019 · outbound

This paper cites Optimality and Stability in Federated Learning: A Game-theoretic Approach.

Strategic Incentivization for Locally Differentially Private Federated Learning Optimality and Stability in Federated Learning: A Game-theoretic Approach

Reference 32

Resolution
verified exact
local_arxiv, observed 2026-08-05T22:25:20.136749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T22:25:20.063012Z digest=sha256:cf0e4e664714efd531dc84ea3a318879454c96486a35df011522b57c70520b8c

Observation e38cd88c-0a8d-4d0c-81d4-f5007360e219 · outbound

This paper cites Stackelberg game approach for resource alloca- tion in device-to-device communication with heterogeneous networks,.

Strategic Incentivization for Locally Differentially Private Federated Learning Stackelberg game approach for resource alloca- tion in device-to-device communication with heterogeneous networks,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:25:20.401784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T22:25:20.066302Z digest=sha256:f4c330a00711de699dc4255a66a4f160037a19c07f6a56829737cd634ab246be

Observation 5c643ce8-7acc-4d27-8b90-05d0e69f0d45 · outbound

This paper cites A game theory-based incentive mechanism for collabora- tive security of federated learning in energy blockchain environment,.

Strategic Incentivization for Locally Differentially Private Federated Learning A game theory-based incentive mechanism for collabora- tive security of federated learning in energy blockchain environment,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:25:20.392243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T22:25:20.069422Z digest=sha256:1b465d44ab66d4c35d6e2bbb372fd42f239ea1949a1d3cc95d55b6a804560427

Observation 9ea2b735-21a6-46b6-8254-387ae250e186 · outbound

This paper cites Decentral and incentivized federated learning frame- works: A systematic literature review,.

Strategic Incentivization for Locally Differentially Private Federated Learning Decentral and incentivized federated learning frame- works: A systematic literature review,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:25:20.380316Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T22:25:20.072443Z digest=sha256:c682879545d528eb448839768a1a3b6679046167873e725f472f948d917ec7df

Observation 43ae0dc5-29f2-4f4d-bdb3-256ba022432c · outbound

This paper cites When federated learning meets game theory: A cooperative framework to secure iiot applications on edge computing,.

Strategic Incentivization for Locally Differentially Private Federated Learning When federated learning meets game theory: A cooperative framework to secure iiot applications on edge computing,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:25:20.368430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T22:25:20.075416Z digest=sha256:b2451f5dcfd39aa458519aee0f3526033e788e912406e7a76ef2826e103dbe2c

Observation 81ac068e-54ad-4fce-be16-87862ab1eff8 · outbound

This paper cites A game-theoretic approach for federated learning: A trade- off among privacy, accuracy and energy,.

Strategic Incentivization for Locally Differentially Private Federated Learning A game-theoretic approach for federated learning: A trade- off among privacy, accuracy and energy,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:25:20.356858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T22:25:20.078691Z digest=sha256:26428bca2af6b6471481336aa71ec9305a51a7345e5755964692d86caead6b8c

Observation 729bc399-4c83-40a8-9648-44baa7481c32 · outbound

This paper cites A game-theoretic approach for robust federated learning,.

Strategic Incentivization for Locally Differentially Private Federated Learning A game-theoretic approach for robust federated learning,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:25:20.343228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T22:25:20.081817Z digest=sha256:faa754ea71ba97e1ca034056da4d9c0eb328415e277831dcf5fcf0f8687a8b80

Observation 2ccaf9b1-1c83-4cd0-a3db-2e69240ff477 · outbound

This paper cites Collaboration in participant-centric federated learning: A game-theoretical perspective,.

Strategic Incentivization for Locally Differentially Private Federated Learning Collaboration in participant-centric federated learning: A game-theoretical perspective,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:25:20.325688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T22:25:20.085592Z digest=sha256:bcfb3b3fd9c2d9294d5704eb943254af0701c7a38f68a8f5ca8a57dc0884cab9

Observation 2b23c3aa-6f93-49c9-94cc-2e9d32d9c12a · outbound

This paper cites an unresolved cited work.

Strategic Incentivization for Locally Differentially Private Federated Learning Unresolved cited work

Reference 40

Resolution
unresolved
raw_fallback, observed 2026-08-05T22:25:20.312606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T22:25:20.088561Z digest=sha256:82a81c67ec08185314107cc1a334ce0eeeea6754f1bbf8743feee02050ccb63a

Observation b7927dfe-c53d-4850-9d49-eb8493ada3cc · outbound

This paper cites an unresolved cited work.

Strategic Incentivization for Locally Differentially Private Federated Learning Unresolved cited work

Reference 41

Resolution
unresolved
raw_fallback, observed 2026-08-05T22:25:20.300205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T22:25:20.091734Z digest=sha256:f29273873c07c65128c525853af6ba88cc06b071dfe9feed03fcc030204e6523

Observation 198addc4-d342-4433-8302-aecd73198cab · outbound

This paper cites an unresolved cited work.

Strategic Incentivization for Locally Differentially Private Federated Learning Unresolved cited work

Reference 42

Resolution
unresolved
raw_fallback, observed 2026-08-05T22:25:20.286770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T22:25:20.094765Z digest=sha256:cf9689d3eae2bb51ed09fc838c51c85e8e371d02f27b8c770970189a9aaf06d4

Observation 818d32f6-b5e1-4e91-bed5-1cd2993f8fee · outbound

This paper cites For the baseline scheme, we considered only use the MNIST dataset, while for the proposed schemes in the paper, we use both the MNIST and CIFAR10 datasets.

Strategic Incentivization for Locally Differentially Private Federated Learning For the baseline scheme, we considered only use the MNIST dataset, while for the proposed schemes in the paper, we use both the MNIST and CIFAR10 datasets

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:25:20.272897Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T22:25:20.098031Z digest=sha256:1b02ac2afe59d9c4dd9dce4cd390e8da337e3f34264f9325059062cb2a0671b6

Observation d0ce1862-8342-408a-a750-ec582766731c · outbound

This paper cites Figure 12 shows the accuracy of clients participating in the experiment same as in Figure 8a but with CIFAR10 dataset.

Strategic Incentivization for Locally Differentially Private Federated Learning Figure 12 shows the accuracy of clients participating in the experiment same as in Figure 8a but with CIFAR10 dataset

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:25:20.260448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T22:25:20.102168Z digest=sha256:acc186c13087544d3ad7163393ad4cca0ba02e02d6b1bac7082fcac09f176460

Pith citing papers

No inbound Pith citation observations are available.