Paper Citation Record · LEDGER

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning

As of 22 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 1 inbound Pith citation observation for arXiv:2502.02038.

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

pith.paper-citation-record.v1
2502.02038 v2

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T13:39:53.302157Z

measured 51 of 51 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-08T20:04:30.942032Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-08T20:05:33.969916Z

Reference resolution

50 of 50 outbound references displayed

verified exact2
verified fuzzy32
unresolved16
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 44a1d6c1-d618-4b40-8033-04dbdf981104 · outbound

This paper cites A survey on federated learning,.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning A survey on federated learning,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:39:53.748169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 94cfe484-53f9-4cbe-97cc-a007e86e5b38 · outbound

This paper cites A Survey of Large Language Models.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning A Survey of Large Language Models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-09T13:39:53.152195Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eda166f2-175d-46e3-a10b-f6427330fac7 · outbound

This paper cites Feashare: Feature sharing for computation correctness in edge preprocessing,.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning Feashare: Feature sharing for computation correctness in edge preprocessing,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:39:53.738914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 147d1db6-7f69-4cbf-90b2-77bdeaa171d1 · outbound

This paper cites Semi-asynchronous online federated crowdsourcing,.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning Semi-asynchronous online federated crowdsourcing,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:39:53.729508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation aa1fa5bd-1942-4f63-aec7-198f29580a1e · outbound

This paper cites Ressfl: A resistance transfer framework for defending model inversion attack in split federated learning,.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning Ressfl: A resistance transfer framework for defending model inversion attack in split federated learning,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-09T13:39:53.161276Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f5071fd5-38ea-4e00-89f5-5ae4fe273768 · outbound

This paper cites Label-only model inversion attacks via knowledge transfer,.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning Label-only model inversion attacks via knowledge transfer,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:39:53.714935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e92281b5-7f5c-4007-b551-29976588869a · outbound

This paper cites Agic: Approximate gradient inversion attack on federated learning,.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning Agic: Approximate gradient inversion attack on federated learning,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:39:53.706303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9ddb1ec7-679e-4479-869d-13cecdf3f2ee · outbound

This paper cites Data and model poisoning backdoor attacks on wireless federated learning, and the defense mechanisms: A comprehensive survey,.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning Data and model poisoning backdoor attacks on wireless federated learning, and the defense mechanisms: A comprehensive survey,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:39:53.697605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 422d9d55-98bf-4508-9a36-022cd495140b · outbound

This paper cites Mpaf: Model poisoning attacks to federated learning based on fake clients,.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning Mpaf: Model poisoning attacks to federated learning based on fake clients,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:39:53.688005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 87d37ef5-2c14-42c1-a431-1bd02df50c1d · outbound

This paper cites Safelearn: Secure aggregation for private federated learning,.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning Safelearn: Secure aggregation for private federated learning,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:39:53.680130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 244ced5a-1953-4de1-9a9f-bb90f79e3cc7 · outbound

This paper cites Efficient and privacy-preserving feature importance-based vertical federated learning,.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning Efficient and privacy-preserving feature importance-based vertical federated learning,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:39:53.672155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d0b857fa-4c49-431a-a718-e01ff5df0202 · outbound

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

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning Ldp-fed: Federated learning with local differential privacy,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:39:53.663534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3815d90d-a1c3-4c9e-841f-0ae8f541c39e · outbound

This paper cites Random Gradient Masking as a Defensive Measure to Deep Leakage in Federated Learning.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning Random Gradient Masking as a Defensive Measure to Deep Leakage in Federated Learning

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-08-09T13:39:53.418788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f450e2d8-0272-4cce-9663-eec143572ac3 · outbound

This paper cites FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-09T13:39:53.189793Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 825866a2-fb3b-4b8f-b5cd-e0d5b9067a98 · outbound

This paper cites Defending against back- doors in federated learning with robust learning rate,.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning Defending against back- doors in federated learning with robust learning rate,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:39:53.654610Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 37cc5747-6be7-4449-8e57-9e9157af9deb · outbound

This paper cites Poisoning with cerberus: Stealthy and colluded backdoor attack against federated learning,.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning Poisoning with cerberus: Stealthy and colluded backdoor attack against federated learning,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:39:53.645714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2b93fff7-9ddd-4fe7-9d6e-e701b7277324 · outbound

This paper cites Roseagg: Robust defense against targeted collusion attacks in federated learning,.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning Roseagg: Robust defense against targeted collusion attacks in federated learning,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:39:53.637005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation fe182978-2f4a-419e-a58f-75a417152daa · outbound

This paper cites Eiffel: Ensuring integrity for federated learning,.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning Eiffel: Ensuring integrity for federated learning,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:39:53.627450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e3e54d4e-1f00-4109-b7fc-70a878836c39 · outbound

This paper cites A survey on federated unlearning: Challenges, methods, and future directions,.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning A survey on federated unlearning: Challenges, methods, and future directions,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-09T13:39:53.206281Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8b7c8056-6778-4c36-a3dd-95a24bc860ca · outbound

This paper cites Detection and incentive: A tampering detection mechanism for object detection in edge computing,.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning Detection and incentive: A tampering detection mechanism for object detection in edge computing,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:39:53.613082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a7585880-315c-4858-bf56-b723a7953723 · outbound

This paper cites Heterogeneous federated knowledge graph embedding learning and unlearning,.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning Heterogeneous federated knowledge graph embedding learning and unlearning,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:39:53.603506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f45f999f-c881-4a27-9967-5aa3f19a4ad6 · outbound

This paper cites Revfrf: Enabling cross-domain random forest training with revocable federated learning,.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning Revfrf: Enabling cross-domain random forest training with revocable federated learning,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:39:53.594296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0fdcdbb5-7cfb-4703-b06b-36673febb1b7 · outbound

This paper cites Verifi: Towards verifiable federated unlearning,.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning Verifi: Towards verifiable federated unlearning,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:39:53.584158Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c31cac37-95fc-4237-ac23-9998ffd8eb59 · outbound

This paper cites Federated Unlearning: How to Efficiently Erase a Client in FL?.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning Federated Unlearning: How to Efficiently Erase a Client in FL?

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-09T13:39:53.221771Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d97fca1-4e03-402f-8d76-a22ff196b198 · outbound

This paper cites A blockchain-based shamir’s threshold cryptography scheme for data protection in industrial internet of things settings,.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning A blockchain-based shamir’s threshold cryptography scheme for data protection in industrial internet of things settings,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:39:53.573907Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d3235944-4466-4987-9aa4-f36816746acd · outbound

This paper cites Edge computing: Vision and chal- lenges,.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning Edge computing: Vision and chal- lenges,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:39:53.564463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 32aaf10c-787e-42db-b1ad-9c3313366f92 · outbound

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

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning Gradient-based learning applied to document recognition,

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-09T13:39:53.231866Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e06c695-7148-451c-93d8-03b96d16dd19 · outbound

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

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-09T13:39:53.235042Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2f32a9d5-2fa0-42c3-a06b-ba5d3b94adf8 · outbound

This paper cites Emnist: Extending mnist to handwritten letters,.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning Emnist: Extending mnist to handwritten letters,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:39:53.550596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 94266a61-c035-40b0-b27c-04e991619f07 · outbound

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

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning Learning multiple layers of features from tiny images,

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-09T13:39:53.241180Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 640c4231-f27d-4ee4-96f8-91f69b484c5e · outbound

This paper cites {FLAME}: Taming backdoors in federated learning,.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning {FLAME}: Taming backdoors in federated learning,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:39:53.538179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation af90d6af-0faa-477f-9619-60b2859f08d6 · outbound

This paper cites Ppfl: Privacy-preserving federated learning with trusted execution environments,.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning Ppfl: Privacy-preserving federated learning with trusted execution environments,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:39:53.530828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0faea231-f9bc-4c8f-bd48-ee045a11eaa8 · outbound

This paper cites BayBFed: Bayesian Backdoor Defense for Federated Learning.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning BayBFed: Bayesian Backdoor Defense for Federated Learning

Reference 33

Resolution: verified exact; local_arxiv, observed 2026-08-09T13:39:53.382040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7b98ff38-5947-4d15-9d31-e011531a041d · outbound

This paper cites Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-09T13:39:53.250759Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 799f3f3c-25f5-4e4c-8f5e-3de7ea6bf8ae · outbound

This paper cites Federated Learning: Strategies for Improving Communication Efficiency.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning Federated Learning: Strategies for Improving Communication Efficiency

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-09T13:39:53.253277Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8bc750b7-e6ab-433c-bcab-7451645beaf5 · outbound

This paper cites Local model poisoning attacks to {Byzantine-Robust} federated learning,.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning Local model poisoning attacks to {Byzantine-Robust} federated learning,

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-09T13:39:53.256300Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 74380fa4-5c66-4ca6-81b0-91c8acf4561e · outbound

This paper cites DeepSight: Mitigating Backdoor Attacks in Federated Learning Through Deep Model Inspection.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning DeepSight: Mitigating Backdoor Attacks in Federated Learning Through Deep Model Inspection

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-09T13:39:53.259427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b97af514-32cc-46a7-801a-83de5dd2d1bc · outbound

This paper cites FreqFed: A Frequency Analysis-Based Approach for Mitigating Poisoning Attacks in Federated Learning.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning FreqFed: A Frequency Analysis-Based Approach for Mitigating Poisoning Attacks in Federated Learning

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-09T13:39:53.262605Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 74c4c16b-5312-4bac-85a9-309f66639d8a · outbound

This paper cites Auror: Defending against poisoning attacks in collaborative deep learning systems,.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning Auror: Defending against poisoning attacks in collaborative deep learning systems,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:39:53.516581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f3f4cb34-432f-4fba-bacc-3bf1ddb3a1e4 · outbound

This paper cites Towards deep learning models resistant to adversarial attacks,.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning Towards deep learning models resistant to adversarial attacks,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:39:53.508147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e6f34589-aab0-4634-ae1d-4b915f76f4e3 · outbound

This paper cites Deep Leakage from Gradients.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning Deep Leakage from Gradients

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-09T13:39:53.272927Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35232b46-0e60-4562-80e3-e9651959291d · outbound

This paper cites Fedrecover: Recovering from poisoning attacks in federated learning using historical information,.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning Fedrecover: Recovering from poisoning attacks in federated learning using historical information,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:39:53.499120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a3d0899b-dc8c-49f2-a409-d8d70aa6bfe0 · outbound

This paper cites Flairs: Fpga-accelerated inference-resistant & secure federated learning,.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning Flairs: Fpga-accelerated inference-resistant & secure federated learning,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:39:53.490210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation adc923ea-002e-44b4-be2f-1c86d7cc0ef1 · outbound

This paper cites Toward robustness and privacy in federated learning: Experimenting with local and central differential privacy,.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning Toward robustness and privacy in federated learning: Experimenting with local and central differential privacy,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:39:53.480725Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 98a6671f-97f9-41e5-8e1d-3421371176df · outbound

This paper cites The limitations of federated learning in sybil settings,.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning The limitations of federated learning in sybil settings,

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-09T13:39:53.285645Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e869d33e-a05e-4a9e-9839-867e876158c3 · outbound

This paper cites Baffle: Backdoor de- tection via feedback-based federated learning,.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning Baffle: Backdoor de- tection via feedback-based federated learning,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:39:53.466295Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation edefd3f2-d019-4d57-826e-f44aa14f6199 · outbound

This paper cites Learning Differentially Private Recurrent Language Models.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning Learning Differentially Private Recurrent Language Models

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-09T13:39:53.291859Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 751cca3c-4e16-4de5-bffd-abffcc0c02c8 · outbound

This paper cites Machine learning with adversaries: byzantine tolerant gradient descent,.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning Machine learning with adversaries: byzantine tolerant gradient descent,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:39:53.457121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b3befb7b-0d70-40f6-9379-db33c72fdb46 · outbound

This paper cites Eluding secure aggregation in federated learning via model inconsistency,.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning Eluding secure aggregation in federated learning via model inconsistency,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:39:53.447865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 11c94e19-5a6e-4bea-9694-7c19d278cf5f · outbound

This paper cites Holodeck: Language guided generation of 3d embodied ai environments,.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning Holodeck: Language guided generation of 3d embodied ai environments,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:39:53.437579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Pith citing papers

Observation 117a77f1-5897-48bd-b7c1-9b7442ca7793 · inbound

SearchEyes: Towards Frontier Multimodal Deep Search Intelligence via Search World Simulation cites this paper.

SearchEyes: Towards Frontier Multimodal Deep Search Intelligence via Search World Simulation SMTFL: Secure Model Training to Untrusted Participants in Federated Learning

Reference 58

Resolution: metadata mismatch; local_arxiv, observed 2026-07-08T20:05:33.971190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.