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Paper Citation Record · LEDGER

Learning Not to Reconstruct Anomalies

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2110.09742.

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

pith.paper-citation-record.v1
2110.09742 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T15:37:16.617557Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T12:34:01.512012Z

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 330517a6-3f89-46f7-961f-974265ca9cfa · inbound

Autoencoders for Anomaly Detection are Unreliable cites this paper.

Autoencoders for Anomaly Detection are Unreliable Learning Not to Reconstruct Anomalies

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-10T15:37:16.617557Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T15:37:16.617557Z digest=sha256:8acbe972b009fdf0f680443ab9a7fdb3ada4d9adffbb67476f561558813b00e8

Observation b4d1dd38-1086-4932-9d26-db6a5a3c2292 · inbound

The Evolution of Video Anomaly Detection: A Unified Framework from DNN to MLLM cites this paper.

The Evolution of Video Anomaly Detection: A Unified Framework from DNN to MLLM Learning Not to Reconstruct Anomalies

Reference 27

Resolution
verified exact
local_arxiv, observed 2026-08-06T12:34:01.515218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T12:34:00.228618Z digest=sha256:4f37de6b0bd97ad787dad6341f4eb195b122ef5f2b28f968ffacba293a0d535e