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Paper Citation Record · LEDGER

LDPTrace: Locally Differentially Private Trajectory Synthesis

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2302.06180.

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

pith.paper-citation-record.v1
2302.06180 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T05:34:14.985466Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T13:38:19.422492Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation e6872c5b-b42d-4f54-8580-0cf750ac1824 · inbound

Data Poisoning Attacks to Local Differential Privacy Protocols for Graphs cites this paper.

Data Poisoning Attacks to Local Differential Privacy Protocols for Graphs LDPTrace: Locally Differentially Private Trajectory Synthesis

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-11T05:34:14.985466Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T05:34:14.985466Z digest=sha256:14d4f52697215a480ef88e4840ec8e4129242afb3806f7ba6940cdb33f51d03d

Observation 895c84d0-2b94-473e-ba75-36925f275f4b · inbound

Private Continuous-Time Synthetic Trajectory Generation via Mean-Field Langevin Dynamics cites this paper.

Private Continuous-Time Synthetic Trajectory Generation via Mean-Field Langevin Dynamics LDPTrace: Locally Differentially Private Trajectory Synthesis

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-07T01:06:21.989017Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T01:06:21.989017Z digest=sha256:dacb46bb22dc2a520a60f030eafe552f6e3d557f312d7663a89edfd8e9e8643c

Observation f0aeaa7f-9cf5-48ad-9315-93be3d6a88cb · inbound

Leveraging the Spatial Hierarchy: Coarse-to-fine Trajectory Generation via Cascaded Hybrid Diffusion cites this paper.

Leveraging the Spatial Hierarchy: Coarse-to-fine Trajectory Generation via Cascaded Hybrid Diffusion LDPTrace: Locally Differentially Private Trajectory Synthesis

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-06T19:27:44.696482Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:27:44.696482Z digest=sha256:251c8821ed48a5bf9c3267f5d2076a4220767eb86627972226ff5efa175a8883

Observation 2258030f-8d6e-45ef-8501-5c10da2bbc29 · inbound

Efficient Prompt Learning for Traffic Forecasting cites this paper.

Efficient Prompt Learning for Traffic Forecasting LDPTrace: Locally Differentially Private Trajectory Synthesis

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-12T08:06:26.772433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-12T01:20:37.192907Z digest=sha256:a427887c72148bc75ef94ba614e357615e4a64d4acf8f23dd16b82c06184270b

Observation 7d2f64b6-da93-42cb-aa04-4f514a5a0400 · inbound

DP-SelFT: Differentially Private Selective Fine-Tuning for Large Language Models cites this paper.

DP-SelFT: Differentially Private Selective Fine-Tuning for Large Language Models LDPTrace: Locally Differentially Private Trajectory Synthesis

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-20T13:38:19.424097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-20T13:35:02.869657Z digest=sha256:c69bc935e3471a86b4f7664894f80ab3000e864aaead45427c5de8ebb7becc30