Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Exploring How Generative Adversarial Networks Learn Phonological Representations
As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2305.12501.
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 2026-08-17T06:30:58.91139+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T20:39:45.002850Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-07T04:57:26.851681Z
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 12633571-9f31-4f0e-b08d-3bd906c634b7 · inbound
Exploring the encoding of linguistic representations in the Fully-Connected Layer of generative CNNs for Speech cites this paper.
Exploring the encoding of linguistic representations in the Fully-Connected Layer of generative CNNs for Speech Exploring How Generative Adversarial Networks Learn Phonological Representations
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T20:39:45.002850Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6dcfe65d-b1b1-422a-95d9-781c483061d3 · inbound
A Technique for Isolating Lexically-Independent Phonetic Dependencies in Generative CNNs cites this paper.
A Technique for Isolating Lexically-Independent Phonetic Dependencies in Generative CNNs Exploring How Generative Adversarial Networks Learn Phonological Representations
Reference 14
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T04:57:26.856240Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.