Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation
As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2106.04399.
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 2026-08-06T06:34:29.942622+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-07-01T16:52:26.323828Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
27
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation cc1e7747-00b1-41c7-afd8-7013e307e433 · inbound
Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution cites this paper.
Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation
Reference 48
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T08:12:31.295643Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 1a496d5e-5412-4c1a-9424-cd97e020d32f · inbound
A Meta Reinforcement Learning Approach to Goals-Based Wealth Management cites this paper.
A Meta Reinforcement Learning Approach to Goals-Based Wealth Management Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation
Reference 258
- Resolution
- verified exact
- arxiv_id, observed 2026-05-08T18:44:01.652301Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 39d05a94-a868-461e-9ab8-7beb1f87b4e6 · inbound
DGLD: Domain-Gated Latent Diffusion for the Discovery of Novel Energetic Materials cites this paper.
DGLD: Domain-Gated Latent Diffusion for the Discovery of Novel Energetic Materials Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation
Reference 6
- Resolution
- verified exact
- arxiv_id, observed 2026-07-01T16:55:50.488782Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.