Paper Citation Record · LEDGER

Meta-Federated Learning: A Novel Approach for Real-Time Traffic Flow Management

As of 14 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 0 inbound Pith citation observations for arXiv:2501.16758.

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

pith.paper-citation-record.v1
2501.16758 v1

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T10:57:58.555055Z

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+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

25 of 25 outbound references displayed

verified exact0
verified fuzzy16
unresolved8
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 66b2f0e8-1f19-44ab-b372-2a099a972246 · outbound

This paper cites Numerical Analysis of a Bimetallic-Based Surface Plasmon Resonance Biosensor for Cancer Detection,.

Meta-Federated Learning: A Novel Approach for Real-Time Traffic Flow Management Numerical Analysis of a Bimetallic-Based Surface Plasmon Resonance Biosensor for Cancer Detection,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-10T10:57:58.415794Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 05ff06b8-61ee-4890-8b98-1df1d69521a5 · outbound

This paper cites A study of permission-based malware detection using machine learning,.

Meta-Federated Learning: A Novel Approach for Real-Time Traffic Flow Management A study of permission-based malware detection using machine learning,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:57:59.000686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 4a5ec2f0-948c-4f69-afb1-57054417ba4a · outbound

This paper cites Multimodal Federated Learning with Model Personalization,.

Meta-Federated Learning: A Novel Approach for Real-Time Traffic Flow Management Multimodal Federated Learning with Model Personalization,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-10T10:57:58.426531Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a1678dc4-aff7-4262-952b-3e0fd5536d63 · outbound

This paper cites Electrical Load Forecasting in Smart Grid: A Personalized Federated Learning Approach.

Meta-Federated Learning: A Novel Approach for Real-Time Traffic Flow Management Electrical Load Forecasting in Smart Grid: A Personalized Federated Learning Approach

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-10T10:57:58.431755Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f45d134c-3b19-4b1d-bdf4-8fe4cab5a27c · outbound

This paper cites Improved modulation recognition using personalized federated learning,.

Meta-Federated Learning: A Novel Approach for Real-Time Traffic Flow Management Improved modulation recognition using personalized federated learning,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-10T10:57:58.437640Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation db0afe7b-0949-4ca2-a09c-d78fffca888a · outbound

This paper cites Federated multi-task learning,.

Meta-Federated Learning: A Novel Approach for Real-Time Traffic Flow Management Federated multi-task learning,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:57:58.963831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 40a1085d-e8ca-40c0-8804-5e161e60ec30 · outbound

This paper cites Federated Learning of a Mixture of Global and Local Models.

Meta-Federated Learning: A Novel Approach for Real-Time Traffic Flow Management Federated Learning of a Mixture of Global and Local Models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-10T10:57:58.448434Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 26afe4fc-8b6e-4e9e-ad45-058167ca9ef8 · outbound

This paper cites Multi-Source Cross-Lingual Model Transfer: Learning What to Share.

Meta-Federated Learning: A Novel Approach for Real-Time Traffic Flow Management Multi-Source Cross-Lingual Model Transfer: Learning What to Share

Reference 8

Resolution: metadata mismatch; local_arxiv, observed 2026-08-10T10:57:58.661801Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 9d80527a-76b2-4ddd-b5b1-5b0bad371c5d · outbound

This paper cites A Survey on Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection,.

Meta-Federated Learning: A Novel Approach for Real-Time Traffic Flow Management A Survey on Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:57:58.948406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d1524006-19f5-4dc2-817e-2bedd7e634d3 · outbound

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

Meta-Federated Learning: A Novel Approach for Real-Time Traffic Flow Management Communication-Efficient Learning of Deep Networks from Decentralized Data

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-10T10:57:58.464583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8dddf58e-a18b-4325-9d9d-dc056bded1f8 · outbound

This paper cites Survey of Personalized Federated Learning: A Taxonomical and Critical Review,.

Meta-Federated Learning: A Novel Approach for Real-Time Traffic Flow Management Survey of Personalized Federated Learning: A Taxonomical and Critical Review,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:57:58.933367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 81f27b74-c6fe-41f3-93ed-7b194f470aa5 · outbound

This paper cites Murray, Feedback Systems: An Introduction for Scientists and Engineers , Princeton University Press, 2010.

Meta-Federated Learning: A Novel Approach for Real-Time Traffic Flow Management Murray, Feedback Systems: An Introduction for Scientists and Engineers , Princeton University Press, 2010

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:57:58.917836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation dd9ff9f0-1953-4d16-8d55-b8c1b119a904 · outbound

This paper cites Convergence of federated learning upon limited communication,.

Meta-Federated Learning: A Novel Approach for Real-Time Traffic Flow Management Convergence of federated learning upon limited communication,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:57:58.902364Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation fd95d878-e5c0-484f-a4ed-1980b4179025 · outbound

This paper cites ”Smart Traffic Management with IoT: A Real-World Application Study.” Journal of Smart City Technology , vol.

Meta-Federated Learning: A Novel Approach for Real-Time Traffic Flow Management ”Smart Traffic Management with IoT: A Real-World Application Study.” Journal of Smart City Technology , vol

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:57:58.886224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation bda501c4-386c-4c5f-8bba-0796c9a3b93f · outbound

This paper cites ”Challenges and Opportunities in Traffic Data Management.” Transportation Research Part C, vol.

Meta-Federated Learning: A Novel Approach for Real-Time Traffic Flow Management ”Challenges and Opportunities in Traffic Data Management.” Transportation Research Part C, vol

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:57:58.869281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation cc0112d7-3aac-46a1-a21b-498740c697c4 · outbound

This paper cites Brendan, et al.

Meta-Federated Learning: A Novel Approach for Real-Time Traffic Flow Management Brendan, et al

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:57:58.852643Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 9a0e3ab9-fd03-46e8-9cb5-0ed945f02d78 · outbound

This paper cites ”Adaptive Traffic Control Systems: The Role of Real-Time Data and Machine Learning.” Journal of Transportation Technologies, vol.

Meta-Federated Learning: A Novel Approach for Real-Time Traffic Flow Management ”Adaptive Traffic Control Systems: The Role of Real-Time Data and Machine Learning.” Journal of Transportation Technologies, vol

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:57:58.796352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f64c47c1-9d33-4e80-93b5-6b3003de5b45 · outbound

This paper cites ”Predictive Models for Traffic Management: A Survey.” IEEE Transactions on Intelligent Transportation Systems , vol.

Meta-Federated Learning: A Novel Approach for Real-Time Traffic Flow Management ”Predictive Models for Traffic Management: A Survey.” IEEE Transactions on Intelligent Transportation Systems , vol

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:57:58.774926Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 1e55e5e9-8b14-4b54-b185-d99801f12325 · outbound

This paper cites Federated Optimization: Distributed Machine Learning for On-Device Intelligence.

Meta-Federated Learning: A Novel Approach for Real-Time Traffic Flow Management Federated Optimization: Distributed Machine Learning for On-Device Intelligence

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-10T10:57:58.525765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation db9fbf63-bb4c-415c-8419-cfff41cc2bd1 · outbound

This paper cites ”Privacy-Preserving Federated Learning in Smart Cities: Opportunities and Challenges.” IEEE Access, vol.

Meta-Federated Learning: A Novel Approach for Real-Time Traffic Flow Management ”Privacy-Preserving Federated Learning in Smart Cities: Opportunities and Challenges.” IEEE Access, vol

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:57:58.756496Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 513a5053-dc80-41a9-8161-31ff61c4fdbb · outbound

This paper cites ”FedTraffic: Federated Learning for Traffic Flow Prediction.” Proceedings of the IEEE International Conference on Smart City Innovations, 2019.

Meta-Federated Learning: A Novel Approach for Real-Time Traffic Flow Management ”FedTraffic: Federated Learning for Traffic Flow Prediction.” Proceedings of the IEEE International Conference on Smart City Innovations, 2019

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:57:58.734401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 06b7f289-5f97-479a-ae1e-caaf5c243926 · outbound

This paper cites ”Model-Agnostic Meta-Learning for Fast Adapta- tion of Deep Networks.” International Conference on Machine Learning, 2017, pp.

Meta-Federated Learning: A Novel Approach for Real-Time Traffic Flow Management ”Model-Agnostic Meta-Learning for Fast Adapta- tion of Deep Networks.” International Conference on Machine Learning, 2017, pp

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:57:58.836712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 1aabee79-918c-4b8e-b9b2-56ad43066201 · outbound

This paper cites On First-Order Meta-Learning Algorithms.

Meta-Federated Learning: A Novel Approach for Real-Time Traffic Flow Management On First-Order Meta-Learning Algorithms

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-10T10:57:58.545205Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation be1681c0-790a-4f8a-a23a-86e289e63054 · outbound

This paper cites ”Meta-Learning in Neural Networks: A Sur- vey.” IEEE Transactions on Pattern Analysis and Machine Intelligence , 2020.

Meta-Federated Learning: A Novel Approach for Real-Time Traffic Flow Management ”Meta-Learning in Neural Networks: A Sur- vey.” IEEE Transactions on Pattern Analysis and Machine Intelligence , 2020

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:57:58.716095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 5d8f9e9e-bbab-4507-be08-a158b41ffd55 · outbound

This paper cites ”MetaFL: On the Convergence of Meta-Learning on Federated Data.” Journal of Machine Learning Research , vol.

Meta-Federated Learning: A Novel Approach for Real-Time Traffic Flow Management ”MetaFL: On the Convergence of Meta-Learning on Federated Data.” Journal of Machine Learning Research , vol

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:57:58.817223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Pith citing papers

No inbound Pith citation observations are available.