Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Bayesian Learning via Neural Schr\"odinger-F\"ollmer Flows
As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2111.10510.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-08T14:44:35.597156Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-10T00:19:46.628629Z
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 723cb7fe-7c31-49b0-951c-fe2d699d9cf5 · inbound
No Trick, No Treat: Pursuits and Challenges Towards Simulation-free Training of Neural Samplers cites this paper.
No Trick, No Treat: Pursuits and Challenges Towards Simulation-free Training of Neural Samplers Bayesian Learning via Neural Schr\"odinger-F\"ollmer Flows
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T14:44:35.597156Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0d689ce5-5c43-4a33-ab78-edf3872d92f4 · inbound
Path Integral Optimiser: Global Optimisation via Neural Schr\"odinger-F\"ollmer Diffusion cites this paper.
Path Integral Optimiser: Global Optimisation via Neural Schr\"odinger-F\"ollmer Diffusion Bayesian Learning via Neural Schr\"odinger-F\"ollmer Flows
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T05:58:16.165486Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3c7ae0be-605e-4ae0-936e-01019a240bf4 · inbound
Annealed Langevin Monte Carlo for Flow ODE Sampling cites this paper.
Annealed Langevin Monte Carlo for Flow ODE Sampling Bayesian Learning via Neural Schr\"odinger-F\"ollmer Flows
Reference 53
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T00:19:46.630031Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.