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Paper Citation Record · LEDGER

Private Continuous-Time Synthetic Trajectory Generation via Mean-Field Langevin Dynamics

As of 19 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 1 inbound Pith citation observation for arXiv:2506.12203.

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

pith.paper-citation-record.v1
2506.12203 v1

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T01:06:22.022074Z

measured 15 of 15 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:14:59.466122Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T18:15:01.374851Z

Reference resolution

14 of 14 outbound references displayed

  • verified exact2
  • verified fuzzy3
  • unresolved9
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ef6933e6-4928-43c4-a3e6-b6c4685ed76f · outbound

This paper cites Privacy-preserving data release leveraging optimal transport and particle gradient descent.

Private Continuous-Time Synthetic Trajectory Generation via Mean-Field Langevin Dynamics Privacy-preserving data release leveraging optimal transport and particle gradient descent

Reference 4

Resolution
verified exact
local_arxiv, observed 2026-08-07T01:06:22.163760Z

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=2026-08-07T01:06:21.985802Z digest=sha256:8348f707d23ff254d8fa6781017337b0ce997eac38ff598b59a89d76386860cb

Observation 6de9c176-b2b7-4658-9b1a-799b5ce04817 · outbound

This paper cites Privacy without Noisy Gradients: Slicing Mechanism for Generative Model Training.

Private Continuous-Time Synthetic Trajectory Generation via Mean-Field Langevin Dynamics Privacy without Noisy Gradients: Slicing Mechanism for Generative Model Training

Reference 7

Resolution
verified exact
local_arxiv, observed 2026-08-07T01:06:22.126346Z

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=2026-08-07T01:06:21.996376Z digest=sha256:efa4a6ce005687126c99f0f0a54fab8ae318adaee34a204b89125589e9ebdff3

Observation 93eae83b-fbe9-4ecd-9c1d-43e4ad18d7da · outbound

This paper cites From the Schr ¨odinger problem to the MongeKantorovich problem.

Private Continuous-Time Synthetic Trajectory Generation via Mean-Field Langevin Dynamics From the Schr ¨odinger problem to the MongeKantorovich problem

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T01:06:22.186512Z

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=2026-08-07T01:06:22.004401Z digest=sha256:bde4916cf7619d5dfaf9419c79014da89c2bbba88233b158008c5a9180f95832

Observation 6cb0fb18-0b66-492b-bca9-9cb984ad797f · outbound

This paper cites Simulation-free Schr\"odinger bridges via score and flow matching.

Private Continuous-Time Synthetic Trajectory Generation via Mean-Field Langevin Dynamics Simulation-free Schr\"odinger bridges via score and flow matching

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-07T01:06:22.014837Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T01:06:22.014837Z digest=sha256:d51a16e9d6845be84a4f4c027326ae9b3f752ddc80f6a7587fac6ec560429113

Observation a4227976-cc00-45e7-9ae5-78bc51d28a66 · outbound

This paper cites Differentially Private Generative Adversarial Network.

Private Continuous-Time Synthetic Trajectory Generation via Mean-Field Langevin Dynamics Differentially Private Generative Adversarial Network

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T01:06:22.018174Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T01:06:22.018174Z digest=sha256:7b366c6b1dfcb9f1358c1cff6d47b1cefbcabd59eea8752fc28307bcfe6587eb

Observation f9637748-2e27-4f19-b23b-8dc4377668b4 · outbound

This paper cites Learning Density Evolution from Snapshot Data.

Private Continuous-Time Synthetic Trajectory Generation via Mean-Field Langevin Dynamics Learning Density Evolution from Snapshot Data

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-07T01:06:22.022074Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T01:06:22.022074Z digest=sha256:690125546f5496e93ea7bebababeb3067b81cb8fac1766cf0a8f20764f93c1c2

Observation 8561303b-8abf-4848-a5eb-e313eeb34f71 · outbound

This paper cites Deep learning with gaussian differential privacy.Harvard data science review, 2020(23):10–1162,.

Private Continuous-Time Synthetic Trajectory Generation via Mean-Field Langevin Dynamics Deep learning with gaussian differential privacy.Harvard data science review, 2020(23):10–1162,

Reference 2007

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T01:06:22.196715Z

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=2026-08-07T01:06:21.978592Z digest=sha256:b9208b34c6407817bf2869bedcd1729a3dbe0d70eae39a16edc3568798b313b4

Observation d27bfcb1-6bbe-444e-bc30-2fa48a7cebbb · outbound

This paper cites Brendan McMahan, Ilya Mironov, Kunal Talwar, and Li Zhang.

Private Continuous-Time Synthetic Trajectory Generation via Mean-Field Langevin Dynamics Brendan McMahan, Ilya Mironov, Kunal Talwar, and Li Zhang

Reference 2018

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T01:06:22.207522Z

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=2026-08-07T01:06:21.975006Z digest=sha256:3b6b52616a28897389690f1f2a02f60666815150e8da077995effc6d5ee21fd8

Observation d53352eb-9e65-4040-9290-c3b487617d0d · outbound

This paper cites LinkedIn's Audience Engagements API: A Privacy Preserving Data Analytics System at Scale.

Private Continuous-Time Synthetic Trajectory Generation via Mean-Field Langevin Dynamics LinkedIn's Audience Engagements API: A Privacy Preserving Data Analytics System at Scale

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-07T01:06:22.008050Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T01:06:22.008050Z digest=sha256:bef65d457c47f87d91a25e6eef30282f6e8b46d74c8bfb03564fb126b3c08a30

Observation 3ab93f0c-565e-4c26-a5be-9aa4fcd44fbc · outbound

This paper cites Multi-marginal Schr\"odinger Bridges with Iterative Reference Refinement.

Private Continuous-Time Synthetic Trajectory Generation via Mean-Field Langevin Dynamics Multi-marginal Schr\"odinger Bridges with Iterative Reference Refinement

Reference 2020

Resolution
unresolved
no resolver link, observed 2026-08-07T01:06:22.011497Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T01:06:22.011497Z digest=sha256:0367922d86b1d88e34271941f47e7681c5a2ee79b1587cf0c722942829110079

Observation 19fcb994-ce9b-4025-aaba-413f4b133fdb · outbound

This paper cites Uniform-in-$N$ log-Sobolev inequality for the mean-field Langevin dynamics with convex energy.

Private Continuous-Time Synthetic Trajectory Generation via Mean-Field Langevin Dynamics Uniform-in-$N$ log-Sobolev inequality for the mean-field Langevin dynamics with convex energy

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-07T01:06:21.982207Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T01:06:21.982207Z digest=sha256:72e98b2d2fafcdb4967eb701b5f357a41d82d0559cf8e8fa3b152aadae75ec4d

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

This paper cites LDPTrace: Locally Differentially Private Trajectory Synthesis.

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 65ac214e-6ecf-4974-a679-d4a593bd89e9 · outbound

This paper cites Differentially Private Release of Israel's National Registry of Live Births.

Private Continuous-Time Synthetic Trajectory Generation via Mean-Field Langevin Dynamics Differentially Private Release of Israel's National Registry of Live Births

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-07T01:06:22.000079Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T01:06:22.000079Z digest=sha256:d9f4538fc4f549821022af5216d3c127cd508aa9b20c81d03f1d9595bafe6a80

Observation 4cc00b5d-3352-483b-927e-035afa777661 · outbound

This paper cites Mirror Mean-Field Langevin Dynamics.

Private Continuous-Time Synthetic Trajectory Generation via Mean-Field Langevin Dynamics Mirror Mean-Field Langevin Dynamics

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-07T01:06:21.992796Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T01:06:21.992796Z digest=sha256:4535d4451b12c166ff3ddf7b0cfb37f8b033e8a2967f38f0fa116ce27c0437fc

Pith citing papers

Observation fc621c3a-ad11-4b8b-886b-20038d2d57d7 · inbound

Convergence Rate of the Solution of Multi-marginal Schrodinger Bridge Problem with Marginal Constraints from SDEs cites this paper.

Convergence Rate of the Solution of Multi-marginal Schrodinger Bridge Problem with Marginal Constraints from SDEs Private Continuous-Time Synthetic Trajectory Generation via Mean-Field Langevin Dynamics

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-08-06T18:15:01.422693Z

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=2026-08-06T18:14:59.466122Z digest=sha256:7e6dd2a408bd513b4630e66e5ec0110b7db2cb80fc1eaf0e97cb998fc8b150ad