Paper Citation Record · LEDGER

Unsupervised Representation Learning by Predicting Random Distances

As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:1912.12186.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
1912.12186 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T15:52:55.685999Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-06-30T09:44:37.866547Z

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 97d4871e-a981-4d52-bbbd-442a2072ba18 · inbound

CITADEL: Continual Anomaly Detection for Enhanced Learning in IoT Intrusion Detection cites this paper.

CITADEL: Continual Anomaly Detection for Enhanced Learning in IoT Intrusion Detection Unsupervised Representation Learning by Predicting Random Distances

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-05T15:52:55.685999Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 33bb2fd2-24a6-4dc1-b1bd-6d564edac156 · inbound

ReTabAD: A Benchmark for Restoring Semantic Context in Tabular Anomaly Detection cites this paper.

ReTabAD: A Benchmark for Restoring Semantic Context in Tabular Anomaly Detection Unsupervised Representation Learning by Predicting Random Distances

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-04T12:50:26.354650Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d7af1eb-fa8d-466f-bbac-e52325ec4be7 · inbound

Calibrating Tabular Anomaly Detection via Optimal Transport cites this paper.

Calibrating Tabular Anomaly Detection via Optimal Transport Unsupervised Representation Learning by Predicting Random Distances

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-05-16T06:50:43.049906Z

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 4ba1c57a-3488-439c-a754-cc637411ee85 · inbound

RGLD: Randomized Global-Local Density Estimation for Tabular Anomaly Detection cites this paper.

RGLD: Randomized Global-Local Density Estimation for Tabular Anomaly Detection Unsupervised Representation Learning by Predicting Random Distances

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-06-30T09:44:37.868059Z

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.