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Paper Citation Record · LEDGER

Analysis of Langevin midpoint methods using an anticipative Girsanov theorem

As of 8 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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:49:28.720562Z digest=sha256:57af9dc66ecddc6a34ae3b4a65e2a50c99c776473f9ba2855f446c9ec7dd076e

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:49:29.547998Z digest=sha256:16d4a01474c268418410be57e1465d1eff0ed7c5bbccfb62c5eb2e21195f9b21

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:49:29.730958Z digest=sha256:e963ab4036623122a23f9deedbe8e2ed1e006e2f72ed04b2909294787eb5859c

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:49:29.296841Z digest=sha256:572071161a9f90bf9f2371eb70dba41bbcae52e19dd0ac2dc3af423e3f38874b

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:49:29.930291Z digest=sha256:9b44dabb316234a42da5bd5f13aa7c9254077361bbad5b2460709972e76f78b8

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=sha256:92583eab4a644f1ee1ec6c43a252faa0ae63ba40cb2344593093a1661230b35f

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:49:29.842640Z digest=sha256:48ff576b8ff827cf735f1283ecbe01e0bbdfc7f47ddf6fb1ae8ef2aed1db1e18

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=sha256:81db7a702ca22d71251efe286f682382d671acaba9c93ca717729b2496e6a06a

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:49:28.864259Z digest=sha256:2b22b4250d090b10709ce548226783fe392b1114f8bd742e6a0ce2d1ebb29fd2

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:49:29.418073Z digest=sha256:f57cc25d8dbfeb35401422c30a60f4579a25b9ece536ec6cb9fd1d511eb20e40

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:49:30.042287Z digest=sha256:81dd5864ca12daba4f25b652e6c5ea7a857118313df10f88553f96cdb0deb272

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=sha256:1be280953f821e9114c9c89eb187bd720240d41b32023d10c007dd17cacabb56

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-25T07:46:49.641026Z digest=sha256:1b4ab4221876c75a374f5fd47d3d139a49a672d36050724439776d03078cdd24