Paper Citation Record · LEDGER

A Reliable Vertical Federated Learning Framework for Traffic State Estimation with Data Selection and Incentive Mechanisms

As of 8 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2506.01285.

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

pith.paper-citation-record.v1
2506.01285 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:53:25.831438Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

31 of 31 outbound references displayed

verified exact0
verified fuzzy31
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e3d592ef-afa2-4ff3-8834-2358b5e2989c · outbound

This paper cites Ising-traffic: Using ising machine learning to predict traffic congestion under uncertainty,.

A Reliable Vertical Federated Learning Framework for Traffic State Estimation with Data Selection and Incentive Mechanisms Ising-traffic: Using ising machine learning to predict traffic congestion under uncertainty,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:53:33.245759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a79a87a8-0231-47e1-945c-714723eb9278 · outbound

This paper cites A traffic flow dependency and dynamics based deep learning aided approach for network-wide traffic speed propagation prediction,.

A Reliable Vertical Federated Learning Framework for Traffic State Estimation with Data Selection and Incentive Mechanisms A traffic flow dependency and dynamics based deep learning aided approach for network-wide traffic speed propagation prediction,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:53:32.980593Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation cd982a1e-6764-4d6d-a690-266a0e2d9ebb · outbound

This paper cites Pigat: Physics-informed graph attention transformer for air traffic state prediction,.

A Reliable Vertical Federated Learning Framework for Traffic State Estimation with Data Selection and Incentive Mechanisms Pigat: Physics-informed graph attention transformer for air traffic state prediction,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:53:32.708432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4d5e1084-0266-4f77-bda0-4a8de7f38246 · outbound

This paper cites Privacy-preserving data fusion for traffic state estimation: A vertical federated learning approach,.

A Reliable Vertical Federated Learning Framework for Traffic State Estimation with Data Selection and Incentive Mechanisms Privacy-preserving data fusion for traffic state estimation: A vertical federated learning approach,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:53:32.451908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2801a7a4-7091-4191-a6f9-98ed53542cd8 · outbound

This paper cites Optimal privacy control for transport network data sharing,.

A Reliable Vertical Federated Learning Framework for Traffic State Estimation with Data Selection and Incentive Mechanisms Optimal privacy control for transport network data sharing,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:53:32.171577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation accc9ba4-d4e9-4a1d-84d3-e52d7342a92a · outbound

This paper cites Federated learning in vehicular edge computing: A selective model aggregation approach,.

A Reliable Vertical Federated Learning Framework for Traffic State Estimation with Data Selection and Incentive Mechanisms Federated learning in vehicular edge computing: A selective model aggregation approach,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:53:31.915633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ae86745a-a8ca-4836-8713-2ede4a7ea1b2 · outbound

This paper cites Vertical federated learning: Concepts, advances, and challenges,.

A Reliable Vertical Federated Learning Framework for Traffic State Estimation with Data Selection and Incentive Mechanisms Vertical federated learning: Concepts, advances, and challenges,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:53:31.627591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7bfcb042-d930-4113-8b94-d26deccaae10 · outbound

This paper cites A novel framework for traffic congestion management at intersections using federated learning and vertical partitioning,.

A Reliable Vertical Federated Learning Framework for Traffic State Estimation with Data Selection and Incentive Mechanisms A novel framework for traffic congestion management at intersections using federated learning and vertical partitioning,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:53:31.277102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b7b09a9c-388d-49b4-a413-7b23f6785efb · outbound

This paper cites A mobility forecasting framework with vertical federated learning,.

A Reliable Vertical Federated Learning Framework for Traffic State Estimation with Data Selection and Incentive Mechanisms A mobility forecasting framework with vertical federated learning,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:53:30.885375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 693841ac-49c7-49bc-aa7d-3eb79b2ac82b · outbound

This paper cites Fedsdg- fs: Efficient and secure feature selection for vertical federated learning,.

A Reliable Vertical Federated Learning Framework for Traffic State Estimation with Data Selection and Incentive Mechanisms Fedsdg- fs: Efficient and secure feature selection for vertical federated learning,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:53:30.593473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9d6a2886-6e24-4aa1-ae84-fa5d55fadb61 · outbound

This paper cites Vf-ps: How to select important participants in vertical federated learning, efficiently and securely?.

A Reliable Vertical Federated Learning Framework for Traffic State Estimation with Data Selection and Incentive Mechanisms Vf-ps: How to select important participants in vertical federated learning, efficiently and securely?

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:53:30.288626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c5c14b99-a86c-4254-af39-92967e8483c2 · outbound

This paper cites Secure feature selection for vertical federated learning in ehealth systems,.

A Reliable Vertical Federated Learning Framework for Traffic State Estimation with Data Selection and Incentive Mechanisms Secure feature selection for vertical federated learning in ehealth systems,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:53:30.018970Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4d094cc9-09cb-4a7d-873d-0765b903d799 · outbound

This paper cites Vertical federated learning-based feature selection with non- overlapping sample utilization,.

A Reliable Vertical Federated Learning Framework for Traffic State Estimation with Data Selection and Incentive Mechanisms Vertical federated learning-based feature selection with non- overlapping sample utilization,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:53:29.719590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 531471ef-6b21-4a1a-ad65-53bf7e618450 · outbound

This paper cites Less-vfl: Communication-efficient feature selection for vertical federated learning,.

A Reliable Vertical Federated Learning Framework for Traffic State Estimation with Data Selection and Incentive Mechanisms Less-vfl: Communication-efficient feature selection for vertical federated learning,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:53:29.442866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d6720022-7420-4574-9f48-6e2f527d1505 · outbound

This paper cites Coalitional federated learning: Improving communication and training on non-iid data with selfish clients,.

A Reliable Vertical Federated Learning Framework for Traffic State Estimation with Data Selection and Incentive Mechanisms Coalitional federated learning: Improving communication and training on non-iid data with selfish clients,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:53:29.292610Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation cf6497a9-8d13-47f2-a18d-c08b4b01619c · outbound

This paper cites Chiron: A robustness-aware incentive scheme for edge learning via hierarchical reinforcement learning,.

A Reliable Vertical Federated Learning Framework for Traffic State Estimation with Data Selection and Incentive Mechanisms Chiron: A robustness-aware incentive scheme for edge learning via hierarchical reinforcement learning,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:53:29.145574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6ef79ecd-71c4-42e6-be3c-1850bb972709 · outbound

This paper cites Rate: Game-theoretic design of sustainable incentive mechanism for federated learning,.

A Reliable Vertical Federated Learning Framework for Traffic State Estimation with Data Selection and Incentive Mechanisms Rate: Game-theoretic design of sustainable incentive mechanism for federated learning,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:53:29.020266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4971e895-7c79-4c98-bde3-54ed78ae4758 · outbound

This paper cites Towards fair graph federated learning via incentive mechanisms,.

A Reliable Vertical Federated Learning Framework for Traffic State Estimation with Data Selection and Incentive Mechanisms Towards fair graph federated learning via incentive mechanisms,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:53:28.817567Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation eccd4cb1-ac1f-4d9b-b8c3-0e9b2cd06cb9 · outbound

This paper cites Context-aware con- sensus algorithm for blockchain-empowered federated learning,.

A Reliable Vertical Federated Learning Framework for Traffic State Estimation with Data Selection and Incentive Mechanisms Context-aware con- sensus algorithm for blockchain-empowered federated learning,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:53:28.678094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 51a3ca83-91f6-4edd-9e8d-31e4c52c5679 · outbound

This paper cites An incentive mechanism of incorporating supervision game for federated learning in autonomous driving,.

A Reliable Vertical Federated Learning Framework for Traffic State Estimation with Data Selection and Incentive Mechanisms An incentive mechanism of incorporating supervision game for federated learning in autonomous driving,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:53:28.499458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7cb7831b-cfc7-4e99-949e-43af6a2a85c5 · outbound

This paper cites A novel contract theory-based incen- tive mechanism for cooperative task-offloading in electrical vehicular networks,.

A Reliable Vertical Federated Learning Framework for Traffic State Estimation with Data Selection and Incentive Mechanisms A novel contract theory-based incen- tive mechanism for cooperative task-offloading in electrical vehicular networks,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:53:28.272802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e185a601-8893-4d94-8efe-bed032105e6e · outbound

This paper cites Intelligent edge computing in internet of vehicles: A joint computation offloading and caching solution,.

A Reliable Vertical Federated Learning Framework for Traffic State Estimation with Data Selection and Incentive Mechanisms Intelligent edge computing in internet of vehicles: A joint computation offloading and caching solution,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:53:28.091838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 96ddf32f-1005-4fc2-8f5e-71c3ab6b16f1 · outbound

This paper cites Dual-side optimization for cost-delay tradeoff in mobile edge computing,.

A Reliable Vertical Federated Learning Framework for Traffic State Estimation with Data Selection and Incentive Mechanisms Dual-side optimization for cost-delay tradeoff in mobile edge computing,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:53:27.912424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4f136dc3-82b6-47af-89c2-2060fe4d6084 · outbound

This paper cites Hierarchical incentive mechanism design for federated machine learning in mobile networks,.

A Reliable Vertical Federated Learning Framework for Traffic State Estimation with Data Selection and Incentive Mechanisms Hierarchical incentive mechanism design for federated machine learning in mobile networks,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:53:27.763112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9da1846e-f948-417e-94ac-d582f352e288 · outbound

This paper cites Mutual information neural estimation,.

A Reliable Vertical Federated Learning Framework for Traffic State Estimation with Data Selection and Incentive Mechanisms Mutual information neural estimation,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:53:27.582506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation de039c63-d583-413e-b428-6b723513c89c · outbound

This paper cites Vertimrf: Differentially private vertical federated data synthesis,.

A Reliable Vertical Federated Learning Framework for Traffic State Estimation with Data Selection and Incentive Mechanisms Vertimrf: Differentially private vertical federated data synthesis,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:53:27.398688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a0d61cef-9883-49ee-8ad3-dfa35957fd84 · outbound

This paper cites Spatio-temporal graph convolutional net- works: A deep learning framework for traffic forecasting,.

A Reliable Vertical Federated Learning Framework for Traffic State Estimation with Data Selection and Incentive Mechanisms Spatio-temporal graph convolutional net- works: A deep learning framework for traffic forecasting,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:53:27.238096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 02471f15-80e6-4b38-a2cd-76c6a985a05f · outbound

This paper cites On the new era of urban traffic monitoring with massive drone data: The pneuma large-scale field experiment,.

A Reliable Vertical Federated Learning Framework for Traffic State Estimation with Data Selection and Incentive Mechanisms On the new era of urban traffic monitoring with massive drone data: The pneuma large-scale field experiment,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:53:27.085033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8bae3729-386f-4616-8356-1ffce3c4255a · outbound

This paper cites Hmm with non-emitting states for map matching,.

A Reliable Vertical Federated Learning Framework for Traffic State Estimation with Data Selection and Incentive Mechanisms Hmm with non-emitting states for map matching,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:53:26.752422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation be3f3e92-4e77-4b7e-b166-38f12c195cc0 · outbound

This paper cites Vehicular blockchain- based collective learning for connected and autonomous vehicles,.

A Reliable Vertical Federated Learning Framework for Traffic State Estimation with Data Selection and Incentive Mechanisms Vehicular blockchain- based collective learning for connected and autonomous vehicles,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:53:26.438340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 53dcf4a6-b5c7-4b19-a5d1-02ae8b48509e · outbound

This paper cites for contributions to game theory and distributed management of autonomous communication networks.

A Reliable Vertical Federated Learning Framework for Traffic State Estimation with Data Selection and Incentive Mechanisms for contributions to game theory and distributed management of autonomous communication networks

Reference 2022

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:53:26.123801Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Pith citing papers

No inbound Pith citation observations are available.