Paper Citation Record · LEDGER

Federated Learning-Distillation Alternation for Resource-Constrained IoT

As of 19 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 1 inbound Pith citation observation for arXiv:2505.20456.

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

pith.paper-citation-record.v1
2505.20456 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:00:35.961677Z

measured 39 of 39 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 2026-08-03T22:11:53.040113Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

38 of 38 outbound references displayed

verified exact3
verified fuzzy28
unresolved7
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b37b502f-9c56-4533-b25a-06118e8bd9ca · outbound

This paper cites Blockchain meets federated learning in healthcare: A systematic review with challenges and opportunities,.

Federated Learning-Distillation Alternation for Resource-Constrained IoT Blockchain meets federated learning in healthcare: A systematic review with challenges and opportunities,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T14:00:31.964813Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6eb860c3-2bf9-4d01-a5f8-92e2bb9af653 · outbound

This paper cites Federated learning with fair incentives and robust aggregation for UA V-aided crowdsens- ing,.

Federated Learning-Distillation Alternation for Resource-Constrained IoT Federated learning with fair incentives and robust aggregation for UA V-aided crowdsens- ing,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:00:42.160036Z

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 fd2fbdc2-092f-4914-adbd-0fde50d1b56c · outbound

This paper cites Massive wireless energy transfer: En- abling sustainable IoT toward 6G era,.

Federated Learning-Distillation Alternation for Resource-Constrained IoT Massive wireless energy transfer: En- abling sustainable IoT toward 6G era,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:00:41.927964Z

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 699ef5c9-64da-4a1d-87d0-c4fdebe9867f · outbound

This paper cites Energy-sustainable IoT connec- tivity: Vision, technological enablers, challenges, and future directions,.

Federated Learning-Distillation Alternation for Resource-Constrained IoT Energy-sustainable IoT connec- tivity: Vision, technological enablers, challenges, and future directions,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T14:00:32.184669Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fce568b4-4c5b-46ab-9e59-41eee1e189d4 · outbound

This paper cites Zero-energy Devices for 6G: Technical Enablers at a Glance.

Federated Learning-Distillation Alternation for Resource-Constrained IoT Zero-energy Devices for 6G: Technical Enablers at a Glance

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:00:36.658559Z

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 c0120d1e-7d17-4a9c-9460-5f06b0168627 · outbound

This paper cites Communication-Efficient On-Device Machine Learning: Federated Distillation and Augmentation under Non-IID Private Data.

Federated Learning-Distillation Alternation for Resource-Constrained IoT Communication-Efficient On-Device Machine Learning: Federated Distillation and Augmentation under Non-IID Private Data

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T14:00:32.394195Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3a31526f-0614-44f3-8f6c-0d1d0f0547e2 · outbound

This paper cites Mix2FLD: Downlink federated learning after uplink federated distillation with two- way mixup,.

Federated Learning-Distillation Alternation for Resource-Constrained IoT Mix2FLD: Downlink federated learning after uplink federated distillation with two- way mixup,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:00:41.684646Z

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 8bd74a50-4761-4c9c-a2c9-706d2c5aa5d3 · outbound

This paper cites Federated knowledge distillation,.

Federated Learning-Distillation Alternation for Resource-Constrained IoT Federated knowledge distillation,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:00:41.510547Z

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 f5f5def0-2f04-47fe-ab08-20993680de67 · outbound

This paper cites Convergence time optimiza- tion for federated learning over wireless networks,.

Federated Learning-Distillation Alternation for Resource-Constrained IoT Convergence time optimiza- tion for federated learning over wireless networks,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T14:00:32.650961Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af3b40ae-2592-49d5-a890-50f7f9582f07 · outbound

This paper cites On the convergence time of federated learning over wireless networks under imperfect CSI,.

Federated Learning-Distillation Alternation for Resource-Constrained IoT On the convergence time of federated learning over wireless networks under imperfect CSI,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:00:41.307439Z

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 cd51e616-3890-43d5-bd8a-49ae67fce598 · outbound

This paper cites Adaptive heterogeneous client sampling for federated learning over wireless networks,.

Federated Learning-Distillation Alternation for Resource-Constrained IoT Adaptive heterogeneous client sampling for federated learning over wireless networks,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:00:41.152535Z

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 c6f539b8-068f-4737-93f3-51ad0504f8ca · outbound

This paper cites Node selection toward faster convergence for federated learning on non-IID data,.

Federated Learning-Distillation Alternation for Resource-Constrained IoT Node selection toward faster convergence for federated learning on non-IID data,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:00:40.957813Z

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 2b87b0c8-3356-4162-8dc7-2446c60cd35b · outbound

This paper cites Communication-efficient federated learning with compensated overlap-FedAvg,.

Federated Learning-Distillation Alternation for Resource-Constrained IoT Communication-efficient federated learning with compensated overlap-FedAvg,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:00:40.672024Z

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 8364686f-ed48-45e6-8733-eb5dfbd6738c · outbound

This paper cites Communication-efficient federated edge learning via optimal proba- bilistic device scheduling,.

Federated Learning-Distillation Alternation for Resource-Constrained IoT Communication-efficient federated edge learning via optimal proba- bilistic device scheduling,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:00:40.381040Z

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 8ee57870-4cc9-47d3-bc4d-5804ee04652b · outbound

This paper cites From 5G to 6G: Has the Time for Modern Random Access Come?.

Federated Learning-Distillation Alternation for Resource-Constrained IoT From 5G to 6G: Has the Time for Modern Random Access Come?

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:00:36.454802Z

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 46ab99e6-0573-4660-a113-2bd4ecc56ae9 · outbound

This paper cites Federated learning with massive random access,.

Federated Learning-Distillation Alternation for Resource-Constrained IoT Federated learning with massive random access,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:00:40.195631Z

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 5d08dcf6-cc4f-4778-a4b8-5b8f08b3c533 · outbound

This paper cites Multiple access in the era of distributed computing and edge intelligence,.

Federated Learning-Distillation Alternation for Resource-Constrained IoT Multiple access in the era of distributed computing and edge intelligence,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:00:39.992393Z

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 b37eb276-e3ba-4aaa-90b6-db9a39d802d3 · outbound

This paper cites Federated learning with multichannel ALOHA,.

Federated Learning-Distillation Alternation for Resource-Constrained IoT Federated learning with multichannel ALOHA,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:00:39.765569Z

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 ef429065-d13b-4af5-94d1-6539ada7e16a · outbound

This paper cites Energy-aware federated learning with distributed user sampling and multichannel ALOHA,.

Federated Learning-Distillation Alternation for Resource-Constrained IoT Energy-aware federated learning with distributed user sampling and multichannel ALOHA,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:00:39.562909Z

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 cb142651-b7ca-437d-88eb-fba5cb99f02e · outbound

This paper cites Multichan- nel ALOHA optimization for federated learning with multiple models,.

Federated Learning-Distillation Alternation for Resource-Constrained IoT Multichan- nel ALOHA optimization for federated learning with multiple models,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:00:39.401391Z

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 70f1c41b-d030-478a-8d92-a2853ec9f7fc · outbound

This paper cites Decentralized federated learning over slotted ALOHA wireless mesh networking,.

Federated Learning-Distillation Alternation for Resource-Constrained IoT Decentralized federated learning over slotted ALOHA wireless mesh networking,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:00:39.193823Z

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 355a332b-6e8b-496e-b093-254df9627651 · outbound

This paper cites Cost-efficient distributed optimization in machine learning over wireless networks,.

Federated Learning-Distillation Alternation for Resource-Constrained IoT Cost-efficient distributed optimization in machine learning over wireless networks,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:00:39.007019Z

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 0ffd5999-fad1-4ced-a137-47c908f2939b · outbound

This paper cites Wireless federated distillation for distributed edge learning with heterogeneous data,.

Federated Learning-Distillation Alternation for Resource-Constrained IoT Wireless federated distillation for distributed edge learning with heterogeneous data,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:00:38.804932Z

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 d95b0f37-6192-4936-9c71-e98c016d6754 · outbound

This paper cites Distillation-based semi-supervised federated learning for communication-efficient collaborative training with non-IID private data,.

Federated Learning-Distillation Alternation for Resource-Constrained IoT Distillation-based semi-supervised federated learning for communication-efficient collaborative training with non-IID private data,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:00:38.645757Z

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 b7d12fd9-c9ff-43f3-83a1-c3e69fa548dc · outbound

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

Federated Learning-Distillation Alternation for Resource-Constrained IoT FedMD: Heterogenous Federated Learning via Model Distillation

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T14:00:34.658378Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0603d0dc-ce87-4776-a460-d2059d15987f · outbound

This paper cites FedED: Federated learning via ensemble distillation for medical relation extraction,.

Federated Learning-Distillation Alternation for Resource-Constrained IoT FedED: Federated learning via ensemble distillation for medical relation extraction,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:00:38.508485Z

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 0106b008-7a6e-409a-9545-b75cfaebfbaa · outbound

This paper cites Selective knowledge sharing for privacy- preserving federated distillation without a good teacher,.

Federated Learning-Distillation Alternation for Resource-Constrained IoT Selective knowledge sharing for privacy- preserving federated distillation without a good teacher,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:00:38.307918Z

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 c7062b40-deba-417c-b426-09a14c8e1db1 · outbound

This paper cites FedDTG:Federated Data-Free Knowledge Distillation via Three-Player Generative Adversarial Networks.

Federated Learning-Distillation Alternation for Resource-Constrained IoT FedDTG:Federated Data-Free Knowledge Distillation via Three-Player Generative Adversarial Networks

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:00:36.196764Z

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 a4f1aa89-64fe-404a-ba42-de50d4dbbb8c · outbound

This paper cites Digital twin enhanced federated reinforcement learning with lightweight knowledge distillation in mobile networks,.

Federated Learning-Distillation Alternation for Resource-Constrained IoT Digital twin enhanced federated reinforcement learning with lightweight knowledge distillation in mobile networks,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:00:38.083127Z

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 a59633ac-2b15-42cf-b9e8-f65b6ad8ce9c · outbound

This paper cites MNIST handwritten digit database,.

Federated Learning-Distillation Alternation for Resource-Constrained IoT MNIST handwritten digit database,

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T14:00:35.179509Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b6f26ae5-76d6-4363-8300-e9b600d99e83 · outbound

This paper cites Energy- optimal mobile cloud computing under stochastic wireless channel,.

Federated Learning-Distillation Alternation for Resource-Constrained IoT Energy- optimal mobile cloud computing under stochastic wireless channel,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:00:37.926189Z

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 4e32e5d5-d972-4a27-ba8f-e9c0a13af683 · outbound

This paper cites Wirelessly powered federated edge learning: Optimal tradeoffs between convergence and power transfer,.

Federated Learning-Distillation Alternation for Resource-Constrained IoT Wirelessly powered federated edge learning: Optimal tradeoffs between convergence and power transfer,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:00:37.712858Z

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 3b47fa6c-50a8-4d08-83f0-a73401f9895c · outbound

This paper cites Batteryless machine-type communications with average channel state information energy beamforming,.

Federated Learning-Distillation Alternation for Resource-Constrained IoT Batteryless machine-type communications with average channel state information energy beamforming,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:00:37.546429Z

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 319923d8-faab-430f-a726-c398e1843afe · outbound

This paper cites Federated learning over energy harvesting wireless networks,.

Federated Learning-Distillation Alternation for Resource-Constrained IoT Federated learning over energy harvesting wireless networks,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:00:37.376552Z

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 86341bb1-c03a-402d-bd5d-4c12e798c8f3 · outbound

This paper cites A 0.5 V BLE transceiver with a 1.9 mW RX achieving -96.4 dBm sensitivity and -27 dBm tolerance for intermodulation from interferers at 6 and 12 MHz offsets,.

Federated Learning-Distillation Alternation for Resource-Constrained IoT A 0.5 V BLE transceiver with a 1.9 mW RX achieving -96.4 dBm sensitivity and -27 dBm tolerance for intermodulation from interferers at 6 and 12 MHz offsets,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:00:37.208119Z

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 bc1522b3-e7de-460b-9152-91c3eb6ddbcd · outbound

This paper cites Federated learning with non-IID data in wireless networks,.

Federated Learning-Distillation Alternation for Resource-Constrained IoT Federated learning with non-IID data in wireless networks,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:00:37.023313Z

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 dfb15b1f-3edd-4446-ae1c-9f4f33f595c1 · outbound

This paper cites Cybertwin assisted wire- less asynchronous federated learning mechanism for edge computing,.

Federated Learning-Distillation Alternation for Resource-Constrained IoT Cybertwin assisted wire- less asynchronous federated learning mechanism for edge computing,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:00:36.844508Z

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 88bbf174-6e91-4c63-8e41-7aadd7a1726a · outbound

This paper cites Energy-efficient federated edge learning with joint communication and computation design,.

Federated Learning-Distillation Alternation for Resource-Constrained IoT Energy-efficient federated edge learning with joint communication and computation design,

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-07T14:00:35.961677Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 9e47f849-93d5-4230-8b45-6edad21d7c67 · inbound

Computation-aware Energy-harvesting Federated Learning with Pipelined Cyclic Scheduling cites this paper.

Computation-aware Energy-harvesting Federated Learning with Pipelined Cyclic Scheduling Federated Learning-Distillation Alternation for Resource-Constrained IoT

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-03T22:11:53.040113Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.