Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
$t^3$-Variational Autoencoder: Learning Heavy-tailed Data with Student's t and Power Divergence
As of 4 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2312.01133.
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 2026-08-04T06:34:03.388597+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-06-30T18:38:22.576078Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-02T00:56:25.130879Z
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 f02238ea-59f8-48eb-acfc-27befff7d662 · inbound
Markov Chain Decoders Overcome the Heavy-Tail Limitations of Lipschitz Generative Models cites this paper.
Markov Chain Decoders Overcome the Heavy-Tail Limitations of Lipschitz Generative Models $t^3$-Variational Autoencoder: Learning Heavy-tailed Data with Student's t and Power Divergence
Reference 16
- Resolution
- verified exact
- arxiv_id, observed 2026-07-01T14:55:48.233752Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation bf798de7-960c-4fe5-a139-1cc8da03f31d · inbound
Self-Regulating Annealing in Heavy-Tailed Diffusion Models cites this paper.
Self-Regulating Annealing in Heavy-Tailed Diffusion Models $t^3$-Variational Autoencoder: Learning Heavy-tailed Data with Student's t and Power Divergence
Reference 16
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T00:56:25.133051Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.