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Paper Citation Record · LEDGER

A Statistical Approach to Assessing Neural Network Robustness

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:1811.07209.

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

pith.paper-citation-record.v1
1811.07209 v4

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 2026-08-19T06:32:44.657259+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T05:14:56.474444Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

18
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 3c8e67b8-ee4e-42f3-9621-986203f0b07c · inbound

Local Linearity of LLMs Enables Activation Steering via Model-Based Linear Optimal Control cites this paper.

Local Linearity of LLMs Enables Activation Steering via Model-Based Linear Optimal Control A Statistical Approach to Assessing Neural Network Robustness

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-07-04T23:24:58.864263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-05-10T02:31:07.932802Z digest=sha256:54d835d4f19000434b89385aa905f46de8331c27d6a513bcae558767a5adde64

Observation 9eeda46c-f119-4db8-b86c-64827486bec7 · inbound

Bounding the Black Box: A Statistical Certification Framework for AI Risk Regulation cites this paper.

Bounding the Black Box: A Statistical Certification Framework for AI Risk Regulation A Statistical Approach to Assessing Neural Network Robustness

Reference 27

Resolution
verified exact
arxiv_id, observed 2026-07-04T23:24:58.864263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-09T21:33:16.967310Z digest=sha256:fcef66fbf75363a503149f74ece0c9b737b4a8960c20b083e795e670d17f9a70

Observation 9a7d2992-a640-4558-8ebe-1d1c3c865649 · inbound

A Survey on the Verification of Reinforcement Learning Policies cites this paper.

A Survey on the Verification of Reinforcement Learning Policies A Statistical Approach to Assessing Neural Network Robustness

Reference 137

Resolution
unresolved
no resolver link, observed 2026-08-02T14:02:56.663291Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T14:02:56.663291Z digest=sha256:7b47ed8591a674d5fef0de36671ae9a010a7232b3696c29393c9c8cdbba84eff

Observation 211359f3-0bd7-49b8-902e-d82c02b4ece7 · inbound

Safe Start: Configuring Optimization Algorithms for Decision-Making under Extreme Risks cites this paper.

Safe Start: Configuring Optimization Algorithms for Decision-Making under Extreme Risks A Statistical Approach to Assessing Neural Network Robustness

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-11T05:14:56.474444Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T05:14:56.474444Z digest=sha256:50f089856f90b84d5dc363603e5cfc1a8fd4b315b9a2a579f8eb0315971bef61