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Paper Citation Record · LEDGER

Excessive Invariance Causes Adversarial Vulnerability

As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1811.00401.

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

pith.paper-citation-record.v1
1811.00401 v4

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 2026-08-06T06:34:29.942622+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-25T13:13:08.101191Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-25T13:15:51.970641Z

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 e0c9f666-feb9-48db-9a51-2c26220e8f4a · inbound

Learning to Find Correlated Features by Maximizing Information Flow in Convolutional Neural Networks cites this paper.

Learning to Find Correlated Features by Maximizing Information Flow in Convolutional Neural Networks Excessive Invariance Causes Adversarial Vulnerability

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-25T13:15:51.973719Z

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.

source=pdf_text observed=2026-05-25T13:13:08.101191Z digest=sha256:bf777cdfa3500a8776b51b8470f28a930725741c1c08d899a7a2f3c538a9bc9f

Observation 0a96aa3a-0951-495d-8237-2070b3497d70 · inbound

Guided Image Generation with Conditional Invertible Neural Networks cites this paper.

Guided Image Generation with Conditional Invertible Neural Networks Excessive Invariance Causes Adversarial Vulnerability

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-05-25T09:35:35.554270Z

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.

source=pdf_text observed=2026-05-25T09:31:24.090056Z digest=sha256:2960ee100530ca2834dc442b0b5fd6cd8394470a9e65f10961885a943203101f