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Paper Citation Record · LEDGER

SVAFD: A Secure and Verifiable Co-Aggregation Protocol for Federated Distillation

As of 17 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2505.13319.

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

pith.paper-citation-record.v1
2505.13319 v2

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:26:48.005704Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

42 of 42 outbound references displayed

  • verified exact1
  • verified fuzzy36
  • unresolved5
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f06649b4-8ac7-4956-8244-6e18e09621b0 · outbound

This paper cites Edge Artificial Intelligence for 6G: Vision, Enabling Technologies, and Applications,.

SVAFD: A Secure and Verifiable Co-Aggregation Protocol for Federated Distillation Edge Artificial Intelligence for 6G: Vision, Enabling Technologies, and Applications,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:26:48.857993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T20:26:47.788545Z digest=sha256:71bf4a21806a1410c510e5481e04949eac00091a13dc30cd5edc9a7bcfe7111d

Observation b61a7171-ea39-4bd3-a3f9-a2f523101601 · outbound

This paper cites Agglomerative federated learning: Empowering larger model training via end-edge-cloud collaboration,.

SVAFD: A Secure and Verifiable Co-Aggregation Protocol for Federated Distillation Agglomerative federated learning: Empowering larger model training via end-edge-cloud collaboration,

Reference 2

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verified fuzzy
raw_fallback, observed 2026-08-15T20:26:48.840243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T20:26:47.794337Z digest=sha256:b474074d8d648bea3d3f5bad9b8423fb46c975ceea54f8ede41938ecf176168a

Observation 3cea5717-3458-4315-b2db-f46d34e10c15 · outbound

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

SVAFD: A Secure and Verifiable Co-Aggregation Protocol for Federated Distillation Federated learning in mobile edge networks: A comprehensive survey,

Reference 3

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verified fuzzy
raw_fallback, observed 2026-08-15T20:26:48.819231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T20:26:47.800322Z digest=sha256:38f4ecac9e42d87c72acb291f4da22f1f7b39883aa1401de99eff36f71fd492f

Observation 53dedcef-768e-4d92-8321-27ba125075fe · outbound

This paper cites Exploring the Distributed Knowledge Congruence in Proxy-data-free Federated Distillation,.

SVAFD: A Secure and Verifiable Co-Aggregation Protocol for Federated Distillation Exploring the Distributed Knowledge Congruence in Proxy-data-free Federated Distillation,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:26:48.801792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T20:26:47.805735Z digest=sha256:52164e14877654af870f998039a8e9365d811304c4138aeb542b2d07119ed8f7

Observation 940fb2e9-2ad7-444a-8eee-f61c0f08aab9 · outbound

This paper cites Knowledge Distillation in Federated Edge Learning: A Survey.

SVAFD: A Secure and Verifiable Co-Aggregation Protocol for Federated Distillation Knowledge Distillation in Federated Edge Learning: A Survey

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-15T20:26:47.810634Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:26:47.810634Z digest=sha256:af760a9a0783912542eac02e6f610e6a90bf44e0077bd45801b0baaeb4d69acb

Observation 14a2eb28-266d-47b9-bfa3-48bcbbfd72fd · outbound

This paper cites Personal- ized edge intelligence via federated self-knowledge distillation,.

SVAFD: A Secure and Verifiable Co-Aggregation Protocol for Federated Distillation Personal- ized edge intelligence via federated self-knowledge distillation,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:26:48.780877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T20:26:47.816085Z digest=sha256:2e9f8c0f402bfbe9a45ab48cd8c9f1db226ed8a47cbbd72755a6c7a89d9641c7

Observation 912402b6-c62b-49fa-af7f-ef76266b38c0 · outbound

This paper cites Selective Knowledge Sharing for Privacy- Preserving Federated Distillation without A Good Teacher,.

SVAFD: A Secure and Verifiable Co-Aggregation Protocol for Federated Distillation Selective Knowledge Sharing for Privacy- Preserving Federated Distillation without A Good Teacher,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:26:48.765617Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T20:26:47.821765Z digest=sha256:6908127acc3ea1d682014618decdb35cf1726a752b3ed4d55146f03cafe52c29

Observation a89a5bfe-09ac-473d-a8ee-1d1eb94d5908 · outbound

This paper cites Breaching FedMD: Image Recovery via Paired-Logits Inversion Attack,.

SVAFD: A Secure and Verifiable Co-Aggregation Protocol for Federated Distillation Breaching FedMD: Image Recovery via Paired-Logits Inversion Attack,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:26:48.747569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T20:26:47.826771Z digest=sha256:9412e675121f3db239d24147025bbbbcf9a71c6d64122ddd6ab0d0521da7acaa

Observation 52d238df-2e09-43d0-a2af-653eabc49d9d · outbound

This paper cites ELSA: Secure Aggregation for Federated Learning with Malicious Actors,.

SVAFD: A Secure and Verifiable Co-Aggregation Protocol for Federated Distillation ELSA: Secure Aggregation for Federated Learning with Malicious Actors,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:26:48.732314Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T20:26:47.831261Z digest=sha256:9b41ad02450b22945d24bb14fc4999e3b99e42e4e908a59f666e1de710f81e4e

Observation 2af75c32-67ce-4edf-b3d3-cd19276dcd21 · outbound

This paper cites RoFL: Robustness of Secure Federated Learning,.

SVAFD: A Secure and Verifiable Co-Aggregation Protocol for Federated Distillation RoFL: Robustness of Secure Federated Learning,

Reference 10

Resolution
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raw_fallback, observed 2026-08-15T20:26:48.714477Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T20:26:47.836822Z digest=sha256:3d91f00ddc18faecc350c4c0e19b86dcfb6ae6b0eb438aeeea88525f53c69913

Observation 5db1a947-f874-4e49-bf84-9824082d4892 · outbound

This paper cites Practical Secure Aggregation for Privacy-Preserving Machine Learning|Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security,.

SVAFD: A Secure and Verifiable Co-Aggregation Protocol for Federated Distillation Practical Secure Aggregation for Privacy-Preserving Machine Learning|Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security,

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-15T20:26:47.841677Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:26:47.841677Z digest=sha256:e45699893d58d5e5daf8e9fce17ea0107021493952fecb25d710662ea98045ef

Observation cc1f4d46-aef3-4b4e-b5d8-25340181b577 · outbound

This paper cites EV-FL: Efficient Verifiable Federated Learning With Weighted Aggregation for Industrial IoT Networks,.

SVAFD: A Secure and Verifiable Co-Aggregation Protocol for Federated Distillation EV-FL: Efficient Verifiable Federated Learning With Weighted Aggregation for Industrial IoT Networks,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:26:48.694381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T20:26:47.846729Z digest=sha256:244b9c050fcf3da15bb6765329ffefb9b5ae21ab3c7b07594b4e360cac2a5e9c

Observation 2103f50d-2e69-44cc-b15f-b44a57350031 · outbound

This paper cites martFL: Enabling Utility-Driven Data Marketplace with a Robust and Verifiable Federated Learning Architecture,.

SVAFD: A Secure and Verifiable Co-Aggregation Protocol for Federated Distillation martFL: Enabling Utility-Driven Data Marketplace with a Robust and Verifiable Federated Learning Architecture,

Reference 13

Resolution
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raw_fallback, observed 2026-08-15T20:26:48.674875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T20:26:47.851701Z digest=sha256:bcf8d9d527aa1e55c0056ce0d7c550f26730030950f9a3dbdfd29b469c30ea30

Observation f007dce3-f56f-4c2d-9158-2b638c33480a · outbound

This paper cites Vcd-fl: Verifiable, collusion-resistant, and dynamic federated learning,.

SVAFD: A Secure and Verifiable Co-Aggregation Protocol for Federated Distillation Vcd-fl: Verifiable, collusion-resistant, and dynamic federated learning,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:26:48.658265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T20:26:47.856272Z digest=sha256:aa2440a3bf0b30e38b9853c05f76426a78ff805b1ffe1aa7941b9a71e43e38b8

Observation 557254c9-4613-44f8-8608-d8c7edd09b33 · outbound

This paper cites Logits poisoning attack in federated distillation,.

SVAFD: A Secure and Verifiable Co-Aggregation Protocol for Federated Distillation Logits poisoning attack in federated distillation,

Reference 15

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verified fuzzy
raw_fallback, observed 2026-08-15T20:26:48.642382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T20:26:47.860836Z digest=sha256:4f5d9b3e285398ca7b5347a6c743a75bbf6e18757d7de7d5e0dceaad4b63945a

Observation 3b605e54-e56d-4e33-8ef8-ebf92e6674f4 · outbound

This paper cites Peak-Controlled Logits Poisoning Attack in Federated Distillation.

SVAFD: A Secure and Verifiable Co-Aggregation Protocol for Federated Distillation Peak-Controlled Logits Poisoning Attack in Federated Distillation

Reference 16

Resolution
verified exact
local_arxiv, observed 2026-08-15T20:26:48.089889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T20:26:47.865185Z digest=sha256:8707a10d8d57212d6fc7d82ebd28d697d9f55aa47fa0e45e2383c7f3a227d310

Observation 1054658d-96e2-4b8b-bfc3-704977c2b4af · outbound

This paper cites Privacy leakage from logits attack and its defense in federated distillation,.

SVAFD: A Secure and Verifiable Co-Aggregation Protocol for Federated Distillation Privacy leakage from logits attack and its defense in federated distillation,

Reference 17

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raw_fallback, observed 2026-08-15T20:26:48.626845Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T20:26:47.870061Z digest=sha256:6e32a8fcaa420b71042c3ced8331a1471f8760e15aabc4a2fe8b87da798300fa

Observation 01e9d2a1-f2ff-4f5a-9f7e-b0e74ace43b9 · outbound

This paper cites Federated Learning with Non-IID Data,.

SVAFD: A Secure and Verifiable Co-Aggregation Protocol for Federated Distillation Federated Learning with Non-IID Data,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:26:48.610887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T20:26:47.874462Z digest=sha256:0ff8a4f0c0d097953f5d333e5db4c5560f197e30d18ea670f2803147cb63ecbe

Observation 2f78a93d-40dd-4841-a0bc-15b1cfaad287 · outbound

This paper cites Privacy- preserving deep learning via additively homomorphic encryption,.

SVAFD: A Secure and Verifiable Co-Aggregation Protocol for Federated Distillation Privacy- preserving deep learning via additively homomorphic encryption,

Reference 19

Resolution
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raw_fallback, observed 2026-08-15T20:26:48.593988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T20:26:47.878770Z digest=sha256:8f18dfdde2f054a627dd673871f88288e86dea5ecaa90efaa9792e5b13be73a3

Observation f08a3f8b-a885-4cf9-a3cb-e5bac2830931 · outbound

This paper cites Secure Neural Network in Federated Learning with Model Aggregation under Multiple Keys,.

SVAFD: A Secure and Verifiable Co-Aggregation Protocol for Federated Distillation Secure Neural Network in Federated Learning with Model Aggregation under Multiple Keys,

Reference 20

Resolution
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raw_fallback, observed 2026-08-15T20:26:48.577793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T20:26:47.883855Z digest=sha256:189f054a10942dc8efaab70c165e3136319679340067493a68939cda50ed2401

Observation 5c351a71-fa20-479c-b8cb-e7e4afd3b836 · outbound

This paper cites Verifiable Privacy-Preserving Federated Learning Under Multiple En- crypted Keys,.

SVAFD: A Secure and Verifiable Co-Aggregation Protocol for Federated Distillation Verifiable Privacy-Preserving Federated Learning Under Multiple En- crypted Keys,

Reference 21

Resolution
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raw_fallback, observed 2026-08-15T20:26:48.560332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T20:26:47.888199Z digest=sha256:bf528a3d896863137769d4796f05a62638d3b75a149b5521984277967c4e18af

Observation 8d1af7c5-9f2b-42a6-9291-ba6c4f52123c · outbound

This paper cites Secure Single-Server Aggregation with (Poly)Logarithmic Overhead,.

SVAFD: A Secure and Verifiable Co-Aggregation Protocol for Federated Distillation Secure Single-Server Aggregation with (Poly)Logarithmic Overhead,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:26:48.542577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T20:26:47.893020Z digest=sha256:9075acc376b0a5e94ec1bb1a79467818a35eddc276dc6149d921904fece09bbf

Observation 35dfb09c-01a5-44e7-a3d0-942cebe78f74 · outbound

This paper cites FLShield: A Validation Based Federated Learning Framework to Defend Against Poisoning Attacks,.

SVAFD: A Secure and Verifiable Co-Aggregation Protocol for Federated Distillation FLShield: A Validation Based Federated Learning Framework to Defend Against Poisoning Attacks,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:26:48.524159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T20:26:47.897847Z digest=sha256:774fc661433957ac27278a50c1c82908d752068511495a8f01116967b3c0f8a3

Observation 799925e7-dcf5-443a-979e-100e09d7498b · outbound

This paper cites Fedcache: A knowledge cache-driven federated learning architecture for personalized edge intelligence,.

SVAFD: A Secure and Verifiable Co-Aggregation Protocol for Federated Distillation Fedcache: A knowledge cache-driven federated learning architecture for personalized edge intelligence,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:26:48.508125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T20:26:47.902458Z digest=sha256:76f9ac9aa29579710ee880f823fb88412b4446b9029e3b440f47942729c9eb16

Observation ec43b9f0-ba70-4dd8-9852-fcd6d148b300 · outbound

This paper cites FedICT: Federated Multi-task Distillation for Multi-access Edge Computing,.

SVAFD: A Secure and Verifiable Co-Aggregation Protocol for Federated Distillation FedICT: Federated Multi-task Distillation for Multi-access Edge Computing,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:26:48.490400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T20:26:47.907133Z digest=sha256:267a4f90d3bf5a083427dffc3c26eecae27992ec85f191e4efb7119f3384bcf6

Observation cec0681b-19f1-429d-8b55-e2d4765896ca · outbound

This paper cites Multi-task federated learning for person- alised deep neural networks in edge computing,.

SVAFD: A Secure and Verifiable Co-Aggregation Protocol for Federated Distillation Multi-task federated learning for person- alised deep neural networks in edge computing,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:26:48.472664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T20:26:47.911666Z digest=sha256:12bb31386ce4d1546ec1520dc56f8dd8939ddac480800a9a653ecff2d663f240

Observation 1d42aec0-de0b-47a8-a6a9-494bf01fd069 · outbound

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

SVAFD: A Secure and Verifiable Co-Aggregation Protocol for Federated Distillation Communication-Efficient On-Device Machine Learning: Federated Dis- tillation and Augmentation under Non-IID Private Data,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:26:48.454082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T20:26:47.916370Z digest=sha256:d467270e09448b54ee9408ef751bb3f4b4bf10b4ad1bef8356cd8259cf1d7551

Observation 8fc5db76-fac0-4c2a-b6ed-2304e0e8d778 · outbound

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

SVAFD: A Secure and Verifiable Co-Aggregation Protocol for Federated Distillation FedMD: Heterogenous Federated Learning via Model Distillation,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:26:48.432014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T20:26:47.921967Z digest=sha256:3e9f49ce1c73f20022c95d8d87a65e67a944f0c59ad0ad179fbba91537ba2661

Observation cb92cf43-ef35-4611-bcc7-8a33d9290228 · outbound

This paper cites Distillation-Based Semi-Supervised Federated Learning for Communication-Efficient Collaborative Training With Non-IID Private Data,.

SVAFD: A Secure and Verifiable Co-Aggregation Protocol for Federated Distillation Distillation-Based Semi-Supervised Federated Learning for Communication-Efficient Collaborative Training With Non-IID Private Data,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:26:48.413119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T20:26:47.926596Z digest=sha256:59880cde69eca6814734f566c638aa13270626b691b2222e4b7a8156a53f2fc4

Observation b2c798f2-815d-4e1c-b458-a8d41dd27194 · outbound

This paper cites Lagrange Coded Computing: Optimal Design for Resiliency, Security and Privacy,.

SVAFD: A Secure and Verifiable Co-Aggregation Protocol for Federated Distillation Lagrange Coded Computing: Optimal Design for Resiliency, Security and Privacy,

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:26:48.393897Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T20:26:47.933625Z digest=sha256:1df002d53f59086cd4e14fe35f0ca48b6d1df98d9d116447fe86bb794cc35b0a

Observation 4d85d194-bc83-462e-bb96-1c029f73db24 · outbound

This paper cites Auction-and-Learning Based Lagrange Coded Computing Model for Privacy-Preserving, Secure, and Resilient Mobile Edge Computing,.

SVAFD: A Secure and Verifiable Co-Aggregation Protocol for Federated Distillation Auction-and-Learning Based Lagrange Coded Computing Model for Privacy-Preserving, Secure, and Resilient Mobile Edge Computing,

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:26:48.373712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T20:26:47.938565Z digest=sha256:602ad738ac17a5631fa00fa03251e1b189b6834cf6811a0e9f875fb91b164c05

Observation a8fdc14f-78a7-47e6-a7e1-1697c29ce708 · outbound

This paper cites Analog Lagrange Coded Computing,.

SVAFD: A Secure and Verifiable Co-Aggregation Protocol for Federated Distillation Analog Lagrange Coded Computing,

Reference 32

Resolution
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raw_fallback, observed 2026-08-15T20:26:48.351390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T20:26:47.943618Z digest=sha256:6501c3a764aa9672d2c67d4cf209d27311dedc0b18f73d3e5210905c6ddd8b66

Observation ad6eaecd-6da0-4942-82c6-417756710181 · outbound

This paper cites DReS-FL: Dropout-resilient secure federated learning for non-IID clients via secret data sharing,.

SVAFD: A Secure and Verifiable Co-Aggregation Protocol for Federated Distillation DReS-FL: Dropout-resilient secure federated learning for non-IID clients via secret data sharing,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:26:48.334187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T20:26:47.949681Z digest=sha256:4df51fed939428b1c88499726160140d981b6f5ccd7d0942c3ece134a8722771

Observation aeae4fec-8b32-47a5-8d81-d9ad2589ed8b · outbound

This paper cites Decentralized federated learning through proxy model sharing,.

SVAFD: A Secure and Verifiable Co-Aggregation Protocol for Federated Distillation Decentralized federated learning through proxy model sharing,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:26:48.316353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T20:26:47.956987Z digest=sha256:9805b181ddc3f80acf2416bf3485ed0b9af6d55a453baf9ba5296e83498b4017

Observation 8d97e4a0-3035-43dc-871a-f72663e72b96 · outbound

This paper cites DFLStar: A Decentralized Federated Learning Framework with Self- Knowledge Distillation and Participant Selection,.

SVAFD: A Secure and Verifiable Co-Aggregation Protocol for Federated Distillation DFLStar: A Decentralized Federated Learning Framework with Self- Knowledge Distillation and Participant Selection,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:26:48.296423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T20:26:47.962544Z digest=sha256:2f26100fbede55db73ab1dc15581af0aa41c60fe9f4db89b1bc814ec561d34c7

Observation 2a656946-562a-4104-b7d8-d59d8ee6686b · outbound

This paper cites Distilling the Knowledge in a Neural Network,.

SVAFD: A Secure and Verifiable Co-Aggregation Protocol for Federated Distillation Distilling the Knowledge in a Neural Network,

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-15T20:26:47.970102Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:26:47.970102Z digest=sha256:63eb38f7c15d2445539d1908d87fbae76d8cc0032aeb569b105f844225707e6f

Observation a8f1477b-f7ed-4a8f-9a80-270b6e7a887f · outbound

This paper cites Similarity search in high dimen- sions via hashing,.

SVAFD: A Secure and Verifiable Co-Aggregation Protocol for Federated Distillation Similarity search in high dimen- sions via hashing,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:26:48.265981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T20:26:47.975959Z digest=sha256:fd01ca415415b26846f5c4ee7607e5d8bf91b680a1245dc660046074cf60a3e7

Observation dd090d21-75eb-4673-900b-a3a34f3a3363 · outbound

This paper cites Privacy- Preserving and Verifiable Outsourcing Linear Inference Computing Framework,.

SVAFD: A Secure and Verifiable Co-Aggregation Protocol for Federated Distillation Privacy- Preserving and Verifiable Outsourcing Linear Inference Computing Framework,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:26:48.246234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T20:26:47.980982Z digest=sha256:1fc7c50dc42067e55780a78143bf13ca204ed6210150f75252830909f2fd9b70

Observation baa97dc0-6bfa-4c2b-bedf-03f5189423e1 · outbound

This paper cites FedML: A Research Library and Benchmark for Federated Machine Learning.

SVAFD: A Secure and Verifiable Co-Aggregation Protocol for Federated Distillation FedML: A Research Library and Benchmark for Federated Machine Learning

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-15T20:26:47.986208Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:26:47.986208Z digest=sha256:5083a6e8acbb3f3b6ac19e933934c85125b11c9f97e2ff48faf94c20991b46c2

Observation 6c759380-bce4-484b-b97a-37e350e6a8c3 · outbound

This paper cites Random projection in dimensionality reduction: applications to image and text data,.

SVAFD: A Secure and Verifiable Co-Aggregation Protocol for Federated Distillation Random projection in dimensionality reduction: applications to image and text data,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:26:48.228374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T20:26:47.991583Z digest=sha256:ca6a97745c4e668359bc4e6c9c06a8fb792bce6f7cba332993e56ec57e360bc6

Observation d548dcc9-1bd8-49c0-b800-3609e63be7e8 · outbound

This paper cites Charm: a framework for rapidly prototyp- ing cryptosystems,.

SVAFD: A Secure and Verifiable Co-Aggregation Protocol for Federated Distillation Charm: a framework for rapidly prototyp- ing cryptosystems,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:26:48.211894Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T20:26:47.997504Z digest=sha256:f61677cb0463f84ccb235194c30610ed9040095e1e1d337f725f3cb2f22a6ab6

Observation 48abfbb9-856e-47da-90fb-7d27f1200694 · outbound

This paper cites Reading digits in natural images with unsupervised feature learning,.

SVAFD: A Secure and Verifiable Co-Aggregation Protocol for Federated Distillation Reading digits in natural images with unsupervised feature learning,

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-15T20:26:48.005704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:26:48.005704Z digest=sha256:364dc1c503266f03590f759ca1a4797a9565d5bcc1d387edec46cda7ab9fb726

Pith citing papers

No inbound Pith citation observations are available.