Paper Citation Record · LEDGER

FedTDP: A Privacy-Preserving and Unified Framework for Trajectory Data Preparation via Federated Learning

As of 17 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 0 inbound Pith citation observations for arXiv:2505.05155.

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

pith.paper-citation-record.v1
2505.05155 v1

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:15:59.653040Z

measured 14 of 14 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

14 of 14 outbound references displayed

verified exact0
verified fuzzy8
unresolved6
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d34288de-9c60-4116-931f-29c84bfab6a0 · outbound

This paper cites Given the number of trajectories|D| in the client, the complexity of Algorithm 2 isO(|D|∗ TR∗ MC ′ ), where MC ′ is the model complexity of the SLM.

FedTDP: A Privacy-Preserving and Unified Framework for Trajectory Data Preparation via Federated Learning Given the number of trajectories|D| in the client, the complexity of Algorithm 2 isO(|D|∗ TR∗ MC ′ ), where MC ′ is the model complexity of the SLM

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:15:59.833960Z

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.

Observation 6c7790e3-0bf1-4247-9823-22c4fab267bc · outbound

This paper cites Open anomalous trajectory recognition via probabilistic metric learning.

FedTDP: A Privacy-Preserving and Unified Framework for Trajectory Data Preparation via Federated Learning Open anomalous trajectory recognition via probabilistic metric learning

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:15:59.903148Z

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.

Observation d4666257-904f-49d6-acb2-d28c8c5e67df · outbound

This paper cites an unresolved cited work.

FedTDP: A Privacy-Preserving and Unified Framework for Trajectory Data Preparation via Federated Learning Unresolved cited work

Reference 4

Resolution: unresolved; raw_fallback, observed 2026-08-15T23:15:59.816941Z

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.

Observation 08ec2075-10f7-46e4-b346-f917de9bb61c · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

FedTDP: A Privacy-Preserving and Unified Framework for Trajectory Data Preparation via Federated Learning LLaMA: Open and Efficient Foundation Language Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-15T23:15:59.603426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e6364ccc-3b35-437e-900c-ce9d24e9517e · outbound

This paper cites Public trans- port planning: When transit network connectivity meets commuting demand.

FedTDP: A Privacy-Preserving and Unified Framework for Trajectory Data Preparation via Federated Learning Public trans- port planning: When transit network connectivity meets commuting demand

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:15:59.885977Z

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.

Observation f2f83a6e-0002-4dd5-8c95-f16df783b58a · outbound

This paper cites Offsite-Tuning: Transfer Learning without Full Model.

FedTDP: A Privacy-Preserving and Unified Framework for Trajectory Data Preparation via Federated Learning Offsite-Tuning: Transfer Learning without Full Model

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-15T23:15:59.614829Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 601e1507-d70c-4e75-aad5-c5a26fbc9b60 · outbound

This paper cites Effective travel time estimation: When historical trajectories over road networks matter.

FedTDP: A Privacy-Preserving and Unified Framework for Trajectory Data Preparation via Federated Learning Effective travel time estimation: When historical trajectories over road networks matter

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:15:59.869628Z

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.

Observation cac824ae-2141-4054-89f9-606102430951 · outbound

This paper cites an unresolved cited work.

FedTDP: A Privacy-Preserving and Unified Framework for Trajectory Data Preparation via Federated Learning Unresolved cited work

Reference 11

Resolution: unresolved; raw_fallback, observed 2026-08-15T23:15:59.760930Z

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.

Observation 419d43da-245e-47a3-bd1f-c1d1504cdbb5 · outbound

This paper cites Baseline We compare the proposed FedTDP framework with state-of-the-art baselines, as shown in Table.

FedTDP: A Privacy-Preserving and Unified Framework for Trajectory Data Preparation via Federated Learning Baseline We compare the proposed FedTDP framework with state-of-the-art baselines, as shown in Table

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:15:59.799754Z

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.

Observation 8a11f390-24fa-489d-ba91-7f5f995c42d2 · outbound

This paper cites • ATROM (Gao et al., 2023).

FedTDP: A Privacy-Preserving and Unified Framework for Trajectory Data Preparation via Federated Learning • ATROM (Gao et al., 2023)

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:15:59.778339Z

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.

Observation ac7189f5-5fa3-4463-84db-8abf7c0ed6be · outbound

This paper cites Qwen Technical Report.

FedTDP: A Privacy-Preserving and Unified Framework for Trajectory Data Preparation via Federated Learning Qwen Technical Report

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-15T23:15:59.580267Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e39ef600-a340-4ba3-80dd-48678713d60e · outbound

This paper cites However, these works are specifically tailored for table data preparation and are not directly applicable to trajectory data preparation tasks.

FedTDP: A Privacy-Preserving and Unified Framework for Trajectory Data Preparation via Federated Learning However, these works are specifically tailored for table data preparation and are not directly applicable to trajectory data preparation tasks

Reference 2022

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:15:59.851641Z

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.

Observation 322e027f-7e1e-4afc-8c4c-bf18e83c34c8 · outbound

This paper cites Gaussian Error Linear Units (GELUs).

FedTDP: A Privacy-Preserving and Unified Framework for Trajectory Data Preparation via Federated Learning Gaussian Error Linear Units (GELUs)

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-15T23:15:59.597129Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a01c632-3719-4ac2-8eff-b8b9f10fd6fe · outbound

This paper cites Personal information protection law of the people’s republic of china.

FedTDP: A Privacy-Preserving and Unified Framework for Trajectory Data Preparation via Federated Learning Personal information protection law of the people’s republic of china

Reference 2024

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:15:59.919717Z

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.

Pith citing papers

No inbound Pith citation observations are available.