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Paper Citation Record · LEDGER

Analysis of Langevin midpoint methods using an anticipative Girsanov theorem

As of 22 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 2026-08-22T06:32:14.747728+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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T16:49:28.720562Z digest=sha256:cc3aaed91501907ed120dac2371970a9c775ef00f5ed966051ad52cc6473d9bd

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T16:49:29.547998Z digest=sha256:187cbb288ac578c3e33341051d4a9a18bf1d281c24795f777edad6e750edf9b0

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T16:49:29.730958Z digest=sha256:ac84be7ee7647870828576b7865603662caff7789f4a551cbce5d6fde1c575b1

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T16:49:29.296841Z digest=sha256:0e0c2c6bb2d089b4ad64c600ff7015a7b824e05e96d260b9e7ed21fcdc1242c7

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T16:49:29.930291Z digest=sha256:20c2709c801a5150fd75e2eb12ff768841a7d1138d6c49e84c534e9b320d37c1

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=sha256:42ab9a386ab18a961c370df8e7eea294209966bfd0328e2201da8142222b64da

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T16:49:29.842640Z digest=sha256:212e48b2c010021694753d5a59760fdf89f941d39cde4c726e4792a79b125f89

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=sha256:024f05d1cebabee317e141443cfacdf7983e521e116cf8fda714e12e161ac0a3

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T16:49:28.864259Z digest=sha256:ca3d03bbbd7df28e286626d83615364b188016b6a83cc337f4e78d47f00c024b

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T16:49:29.418073Z digest=sha256:1deaa096297f5b8ac1f2ac90fda10534428bae9748ba28fd48452a681759bd6b

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T16:49:30.042287Z digest=sha256:39f4f7be2acf1af622aafea28eb36af571338ac367044db8ebb7a57e94fcc467

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=sha256:928163410ba13626ba5b585fd3a34042feb9379e52cab18211e76540343e9c00

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-25T07:46:49.641026Z digest=sha256:6d3f1a6ba5089cdd2d24c72d17ec5ac148e021eceb0ceab8d8f00799350396e4