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Paper Citation Record · LEDGER

Characterizing the Decision Boundary of Deep Neural Networks

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:1912.11460.

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

pith.paper-citation-record.v1
1912.11460 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T13:21:27.572891Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T13:24:53.326967Z

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 e5009e84-0cb0-4c3b-bb2c-910903a3795f · inbound

Dataset Ownership Verification in Contrastive Pre-trained Models cites this paper.

Dataset Ownership Verification in Contrastive Pre-trained Models Characterizing the Decision Boundary of Deep Neural Networks

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-08T13:21:27.572891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T13:21:27.572891Z digest=sha256:97ccaa783e46ae590c94d1f416921b90261102409d934562713dc3555d577775

Observation ba0d7ae1-0595-41dc-b616-f347ee058694 · inbound

Decision Potential Surface: A Theoretical and Practical Approximation of Large Language Model Decision Boundary cites this paper.

Decision Potential Surface: A Theoretical and Practical Approximation of Large Language Model Decision Boundary Characterizing the Decision Boundary of Deep Neural Networks

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-22T13:24:53.329683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-22T13:22:37.107679Z digest=sha256:1d95ca8fa6d41c74fca95a55f94da538c03588f38430e43f5549fde390befb63

Observation 16de7c72-e78d-4e5e-a4c2-f86e082ac737 · inbound

The Confusion is Real: GRAPHIC -- A Network Science Approach to Confusion Matrices in Deep Learning cites this paper.

The Confusion is Real: GRAPHIC -- A Network Science Approach to Confusion Matrices in Deep Learning Characterizing the Decision Boundary of Deep Neural Networks

Reference 7

Resolution
metadata mismatch
arxiv_id, observed 2026-05-15T20:20:17.736278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-15T20:18:20.610845Z digest=sha256:d7089f2df1b478f4a45007b77894025a8a4b7e7a796bc76b6928a0dc53dbe28a

Observation 971c7238-bc08-40e8-b8e5-5662664bbf70 · inbound

On the Decompositionality of Neural Networks cites this paper.

On the Decompositionality of Neural Networks Characterizing the Decision Boundary of Deep Neural Networks

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-11T05:55:57.074243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T17:53:49.835875Z digest=sha256:4ae391b79b79156280da99a23612d53a8ac12eb195cf38ee1254dc7f5fded112

Observation dfb31d04-11cc-46db-ab2d-3627ce846c3f · inbound

Fast and Lightweight Backdoor Detection via Head Random Probing cites this paper.

Fast and Lightweight Backdoor Detection via Head Random Probing Characterizing the Decision Boundary of Deep Neural Networks

Reference 18

Resolution
metadata mismatch
arxiv_id, observed 2026-05-20T12:43:17.529648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-20T12:39:19.973387Z digest=sha256:96b41631097ff2245e9d5694a108b6c4d29f0b1bd050020cc01d903922469d42