Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Latent Space Explorer: Visual Analytics for Multimodal Latent Space Exploration
As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2312.00857.
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 2026-08-11T06:34:44.6726+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T10:51:03.210534Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-11T10:51:03.361156Z
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 0fc88fef-8009-49e2-ab63-52b418beccd1 · inbound
Explainable AI for Multivariate Time Series Pattern Exploration: Latent Space Visual Analytics with Temporal Fusion Transformer and Variational Autoencoders in Power Grid Event Diagnosis cites this paper.
Explainable AI for Multivariate Time Series Pattern Exploration: Latent Space Visual Analytics with Temporal Fusion Transformer and Variational Autoencoders in Power Grid Event Diagnosis Latent Space Explorer: Visual Analytics for Multimodal Latent Space Exploration
Reference 2023
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-11T10:51:03.370433Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 28c0f34d-1335-4bbf-8860-da1b152b2906 · inbound
Unlocking Latent Dimensions: Exploring Representations of Large-Scale X-ray Scattering Data using Variational Autoencoders cites this paper.
Unlocking Latent Dimensions: Exploring Representations of Large-Scale X-ray Scattering Data using Variational Autoencoders Latent Space Explorer: Visual Analytics for Multimodal Latent Space Exploration
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T11:26:35.469329Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.