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Paper Citation Record · LEDGER

Analysis of Langevin midpoint methods using an anticipative Girsanov theorem

As of 9 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 1 inbound Pith citation observation for arXiv:2507.12791.

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

pith.paper-citation-record.v1
2507.12791 v1

Coverage vector

measured 12 of 12 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:49:30.261633Z

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-25T07:46:49.641026Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-25T07:50:29.490995Z

Reference resolution

12 of 12 outbound references displayed

  • verified exact4
  • verified fuzzy5
  • unresolved3
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f8823fa6-10b5-4c32-a28f-e17d362f0cd0 · outbound

This paper cites Shifted Composition II: Shift Harnack Inequalities and Curvature Upper Bounds.

Analysis of Langevin midpoint methods using an anticipative Girsanov theorem Shifted Composition II: Shift Harnack Inequalities and Curvature Upper Bounds

Reference 1

Resolution
verified exact
local_arxiv, observed 2026-08-06T16:49:31.676561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:49:28.720562Z digest=sha256:0c310cad155c89c7a5dadf09bff36f0fa451c41f3cbaa3dc37befe096ea83ed8

Observation 470862a1-4caa-40b4-99b2-6af7a32b7fe2 · outbound

This paper cites Itˆ o formula and Girsanov theorem for anticipating stochastic integrals.

Analysis of Langevin midpoint methods using an anticipative Girsanov theorem Itˆ o formula and Girsanov theorem for anticipating stochastic integrals

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:49:32.923625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:49:29.547998Z digest=sha256:63968ebfcac8f211e993076fae6f157a0751f8308c6f001a13a595a3a6c575e5

Observation 6672fe6d-e308-4f14-95d4-458a17e65adb · outbound

This paper cites The non-linear transformation of Gaussian measure on Banach spaces and its absolute continuity (1).

Analysis of Langevin midpoint methods using an anticipative Girsanov theorem The non-linear transformation of Gaussian measure on Banach spaces and its absolute continuity (1)

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:49:32.706598Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:49:29.730958Z digest=sha256:2850d2527641a826a80e8dbba5944c7c1d4f76723d954e65332ab8415efb1834

Observation 7a5867ac-0b8c-4b7f-a036-52352fe82699 · outbound

This paper cites Implicit Langevin algorithms for sampling from log-concave densities.

Analysis of Langevin midpoint methods using an anticipative Girsanov theorem Implicit Langevin algorithms for sampling from log-concave densities

Reference 9

Resolution
verified exact
raw_fallback, observed 2026-08-06T16:49:31.146472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:49:29.296841Z digest=sha256:9ed493387f8362fbb9dee2d8ef2e082d52e960074da893c1823ad43b1b73ff81

Observation 61b0754b-09a1-4997-9ac9-47a9549dba8a · outbound

This paper cites Applications of anticipating stochastic calculus to stochastic differential equations.

Analysis of Langevin midpoint methods using an anticipative Girsanov theorem Applications of anticipating stochastic calculus to stochastic differential equations

Reference 10

Resolution
verified exact
raw_fallback, observed 2026-08-06T16:49:30.773860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:49:29.930291Z digest=sha256:fbc12e77863a84b606c0ac8b43242a346d6d1e834d3dc2a5ca641d4a982c0798

Observation 230d51b5-a8af-4d55-828c-32e937cf612c · outbound

This paper cites Stochastic Runge-Kutta Methods: Provable Acceleration of Diffusion Models.

Analysis of Langevin midpoint methods using an anticipative Girsanov theorem Stochastic Runge-Kutta Methods: Provable Acceleration of Diffusion Models

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-06T16:49:30.261633Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:49:30.261633Z digest=sha256:7c4efc7a825657e59a4dc2a55e526b10083104eb495dcbd35ee905c445ecc626

Observation a3189861-4762-4093-a61b-d885e4d089ba · outbound

This paper cites Stochastic Runge–Kutta accelerates Langevin Monte Carlo and beyond.

Analysis of Langevin midpoint methods using an anticipative Girsanov theorem Stochastic Runge–Kutta accelerates Langevin Monte Carlo and beyond

Reference 530

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:49:32.409735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:49:29.842640Z digest=sha256:71027de8ec48ab9a7f57f485b4a9be8c616cc156bf38555505e9ee455784cecf

Observation 82cde2c7-601d-4734-87b1-edc3d53f69d2 · outbound

This paper cites When does Metropolized Hamiltonian Monte Carlo provably outperform Metropolis-adjusted Langevin algorithm?.

Analysis of Langevin midpoint methods using an anticipative Girsanov theorem When does Metropolized Hamiltonian Monte Carlo provably outperform Metropolis-adjusted Langevin algorithm?

Reference 1994

Resolution
unresolved
no resolver link, observed 2026-08-06T16:49:28.986813Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:49:28.986813Z digest=sha256:8dd1431619a2dd4b7b6b9956274fd192d25c180a9c81255d5e7b0bafa4fe4266

Observation 816bc90c-5c24-4816-92df-fb4f58a70420 · outbound

This paper cites Nonlinear Hamiltonian Monte Carlo & its Particle Approximation.

Analysis of Langevin midpoint methods using an anticipative Girsanov theorem Nonlinear Hamiltonian Monte Carlo & its Particle Approximation

Reference 2008

Resolution
verified exact
local_arxiv, observed 2026-08-06T16:49:31.524683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:49:28.864259Z digest=sha256:0f91e2b5a734f145ae20376941055518b3b20727d0aa21e599f208907f836c73

Observation 8dcb90e9-18b8-4971-9de6-48a26749cfad · outbound

This paper cites Generalization of the anticipative Girsanov theorem.

Analysis of Langevin midpoint methods using an anticipative Girsanov theorem Generalization of the anticipative Girsanov theorem

Reference 2012

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:49:33.117772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:49:29.418073Z digest=sha256:cb415587ec7ebfcd886982827f76240d949cbb7a9f405e5d785c3f92bedee9fe

Observation 6f79a1a1-fcf0-416d-9f94-e4587e1aee43 · outbound

This paper cites Transformation of Wiener measure under anticipative flows.

Analysis of Langevin midpoint methods using an anticipative Girsanov theorem Transformation of Wiener measure under anticipative flows

Reference 2013

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:49:31.977707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:49:30.042287Z digest=sha256:93679d9e90c063c40c1f764761f0bfa2ca60b368c8f85b96a2778f0511bb4fa9

Observation 660b1516-1a73-4669-bb2a-f65393c2a9a5 · outbound

This paper cites Complexity of randomized algorithms for underdamped Langevin dynamics.

Analysis of Langevin midpoint methods using an anticipative Girsanov theorem Complexity of randomized algorithms for underdamped Langevin dynamics

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-06T16:49:29.190505Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:49:29.190505Z digest=sha256:03f4ffd7d8545d45a3c17338c62a3e0768cfa4bd3925ac8e0ea24571f955d729

Pith citing papers

Observation 0ef97f34-d71b-4940-a509-416dbe1ba25f · inbound

Long-time reverse transportation inequalities for non-globally-dissipative Langevin dynamics cites this paper.

Long-time reverse transportation inequalities for non-globally-dissipative Langevin dynamics Analysis of Langevin midpoint methods using an anticipative Girsanov theorem

Reference 41

Resolution
verified exact
arxiv_id, observed 2026-05-25T07:50:29.493462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-25T07:46:49.641026Z digest=sha256:7a41465630ca307e4f3f0c3b4a082d8b7e04fcb91100272ab62ada7a0d2e1149