Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
A theory of continuous generative flow networks
As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2301.12594.
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 2026-08-12T06:34:41.77262+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T19:09:54.666658Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-07-07T20:54:05.440469Z
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 7e07002a-76f2-4c2a-bd67-f1a2a7bd2045 · inbound
Effective Reward Specification in Deep Reinforcement Learning cites this paper.
Effective Reward Specification in Deep Reinforcement Learning A theory of continuous generative flow networks
Reference 178
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T19:09:54.666658Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3288098d-ae64-49db-90d5-6fcc3174f33a · 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 A theory of continuous generative flow networks
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T14:44:35.576159Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 066689af-5ab9-4982-98de-478814cb02ad · inbound
A Distributional Framework for Generative Modeling of Molecular Crystals cites this paper.
A Distributional Framework for Generative Modeling of Molecular Crystals A theory of continuous generative flow networks
Reference 12
- Resolution
- verified exact
- local_arxiv, observed 2026-07-07T20:54:05.442871Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.