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Paper Citation Record · LEDGER

Action-Minimization Meets Generative Modeling: Efficient Transition Path Sampling with the Onsager-Machlup Functional

As of 4 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2504.18506.

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

pith.paper-citation-record.v1
2504.18506 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-03T06:30:56.289259+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-25T05:20:13.184992Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-25T05:20:24.309411Z

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 a914c1b2-dd12-42ce-a62b-0b262d3fb390 · inbound

A Priori Sampling of Transition States with Guided Diffusion cites this paper.

A Priori Sampling of Transition States with Guided Diffusion Action-Minimization Meets Generative Modeling: Efficient Transition Path Sampling with the Onsager-Machlup Functional

Reference 48

Resolution
metadata mismatch
arxiv_id, observed 2026-05-14T23:58:19.031193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

source=pdf_text observed=2026-05-14T23:54:03.299196Z digest=sha256:901dca63141806d805f00cb52be65531b6bccba34a529fa6b4ad6e3e7e87ceb1

Observation 61265fa7-b4d1-4ee1-934d-6cbfb778a83f · inbound

Energy-oriented Diffusion Bridge for Image Restoration with Foundational Diffusion Models cites this paper.

Energy-oriented Diffusion Bridge for Image Restoration with Foundational Diffusion Models Action-Minimization Meets Generative Modeling: Efficient Transition Path Sampling with the Onsager-Machlup Functional

Reference 8

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T10:01:00.956141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

source=pdf_text observed=2026-05-10T15:42:20.477173Z digest=sha256:2d6c4e16790d1106e9276f1e6de537d7f36eead9e8c177a7f98ed86dfbfa6add

Observation d7dc553f-d7b1-48b3-995e-32b66b3e6810 · inbound

A Call to Lagrangian Action: Learning Population Mechanics from Temporal Snapshots cites this paper.

A Call to Lagrangian Action: Learning Population Mechanics from Temporal Snapshots Action-Minimization Meets Generative Modeling: Efficient Transition Path Sampling with the Onsager-Machlup Functional

Reference 7

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T08:06:27.270219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

source=arxiv_source observed=2026-05-12T01:20:12.816671Z digest=sha256:afb30be93c501c3ec9a2c0359b6123531ccfff1ac3e6dc80e4c0384406dae91d

Observation 0e1a8aea-1684-4b60-9c63-896cdd6c0b68 · inbound

A Call to Lagrangian Action: Learning Population Mechanics from Temporal Snapshots cites this paper.

A Call to Lagrangian Action: Learning Population Mechanics from Temporal Snapshots Action-Minimization Meets Generative Modeling: Efficient Transition Path Sampling with the Onsager-Machlup Functional

Reference 7

Resolution
metadata mismatch
arxiv_id, observed 2026-05-14T20:52:59.225758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

source=arxiv_source observed=2026-05-14T20:49:26.890463Z digest=sha256:fde8ec07abe4d230bc1b4b0367bc6e017d4955eb62b89574c01665a293784460

Observation aefe2cae-e1d5-4c1b-a678-681be6ee588d · inbound

A Call to Lagrangian Action: Learning Population Mechanics from Temporal Snapshots cites this paper.

A Call to Lagrangian Action: Learning Population Mechanics from Temporal Snapshots Action-Minimization Meets Generative Modeling: Efficient Transition Path Sampling with the Onsager-Machlup Functional

Reference 7

Resolution
metadata mismatch
arxiv_id, observed 2026-05-20T22:23:48.172348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

source=arxiv_source observed=2026-05-20T22:20:03.150386Z digest=sha256:b4065d95e480d3024a6a730462696590ff4589ff1c5909b2918d68221c05c960

Observation 79166ed1-193a-4059-9303-176f00815859 · inbound

Information as Maximum-Caliber Deviation: A bridge between Integrated Information Theory and the Free Energy Principle cites this paper.

Information as Maximum-Caliber Deviation: A bridge between Integrated Information Theory and the Free Energy Principle Action-Minimization Meets Generative Modeling: Efficient Transition Path Sampling with the Onsager-Machlup Functional

Reference 201

Resolution
metadata mismatch
arxiv_id, observed 2026-05-14T21:18:00.224140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

source=pdf_text observed=2026-05-14T21:10:27.871783Z digest=sha256:9bf1066b1a69e804dfa836243a8370e5062160da9c871028723eb1a23de29175

Observation c5355b5d-3199-4775-b14e-2fb7881dea38 · inbound

Drift-React: One-step Generation of Reaction Pathways via SE(3) Drifting Fields cites this paper.

Drift-React: One-step Generation of Reaction Pathways via SE(3) Drifting Fields Action-Minimization Meets Generative Modeling: Efficient Transition Path Sampling with the Onsager-Machlup Functional

Reference 33

Resolution
verified exact
arxiv_id, observed 2026-05-25T05:20:24.312700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

source=pdf_text observed=2026-05-25T05:20:13.184992Z digest=sha256:d82197311422640bdcedcf64e99c1f92f93192d8771cdc2bec824ff14ae0b069

Observation 67d96f6b-3fab-4bdf-8c2b-1a4b07e6dd99 · inbound

Onsager-Machlup Posterior Transport for Deep Gaussian Processes cites this paper.

Onsager-Machlup Posterior Transport for Deep Gaussian Processes Action-Minimization Meets Generative Modeling: Efficient Transition Path Sampling with the Onsager-Machlup Functional

Reference 28

Resolution
metadata mismatch
arxiv_id, observed 2026-05-25T04:50:21.090831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

source=arxiv_source observed=2026-05-25T04:48:29.473332Z digest=sha256:9f061c26cf545e3274cba4847428c71870ebdfba6d121b49a16414c6a4ba5222