Paper Citation Record · LEDGER

Fast and Complete: Enabling Complete Neural Network Verification with Rapid and Massively Parallel Incomplete Verifiers

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2011.13824.

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

pith.paper-citation-record.v1
2011.13824 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:09:06.756849Z

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

60
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 2767abf3-9192-4cef-a3f2-d5180c25c90d · inbound

Conformal Mixed-Integer Constraint Learning with Feasibility Guarantees cites this paper.

Conformal Mixed-Integer Constraint Learning with Feasibility Guarantees Fast and Complete: Enabling Complete Neural Network Verification with Rapid and Massively Parallel Incomplete Verifiers

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T11:09:06.756849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ae1d90d7-9770-4730-a2af-b1ac1909edcd · inbound

Formal Verification of Variational Quantum Circuits cites this paper.

Formal Verification of Variational Quantum Circuits Fast and Complete: Enabling Complete Neural Network Verification with Rapid and Massively Parallel Incomplete Verifiers

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-06T17:43:23.040910Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 12978dff-ecb1-4a67-8347-79233638af96 · inbound

Learning to Optimize by Differentiable Programming cites this paper.

Learning to Optimize by Differentiable Programming Fast and Complete: Enabling Complete Neural Network Verification with Rapid and Massively Parallel Incomplete Verifiers

Reference 177

Resolution: unresolved; no resolver link, observed 2026-08-03T08:39:45.848507Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2ca7604c-5be6-4b21-a691-d2f8cdb5c51c · inbound

GeoCert: Certified Geometric AI for Reliable Forecasting cites this paper.

GeoCert: Certified Geometric AI for Reliable Forecasting Fast and Complete: Enabling Complete Neural Network Verification with Rapid and Massively Parallel Incomplete Verifiers

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:41:13.924127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 55f45111-59c0-4ed5-8464-1b91f1f97119 · inbound

Hierarchical End-to-End Taylor Bounds for Complete Neural Network Verification cites this paper.

Hierarchical End-to-End Taylor Bounds for Complete Neural Network Verification Fast and Complete: Enabling Complete Neural Network Verification with Rapid and Massively Parallel Incomplete Verifiers

Reference 15

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T05:56:26.877290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation df594802-bcf5-496d-9e7f-c805a21033e7 · inbound

Quantitative Linear Logic for Neuro-Symbolic Learning and Verification cites this paper.

Quantitative Linear Logic for Neuro-Symbolic Learning and Verification Fast and Complete: Enabling Complete Neural Network Verification with Rapid and Massively Parallel Incomplete Verifiers

Reference 130

Resolution: verified exact; arxiv_id, observed 2026-05-14T17:32:30.581466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d9485b93-b743-4a4d-8e6c-1e8616f9a5fe · inbound

Quantitative Linear Logic for Neuro-Symbolic Learning and Verification cites this paper.

Quantitative Linear Logic for Neuro-Symbolic Learning and Verification Fast and Complete: Enabling Complete Neural Network Verification with Rapid and Massively Parallel Incomplete Verifiers

Reference 130

Resolution: verified exact; arxiv_id, observed 2026-05-15T05:45:05.048925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 13a55bfe-f73a-4b0d-bc18-d92ace8861ba · inbound

Stress-Testing Neural Network Verifiers with Provably Robust Instances cites this paper.

Stress-Testing Neural Network Verifiers with Provably Robust Instances Fast and Complete: Enabling Complete Neural Network Verification with Rapid and Massively Parallel Incomplete Verifiers

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-20T14:53:23.488250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 423706a3-21c0-46bd-a359-aeeae437162b · inbound

Neural Network Verification using Partial Multi-Neuron Relaxation cites this paper.

Neural Network Verification using Partial Multi-Neuron Relaxation Fast and Complete: Enabling Complete Neural Network Verification with Rapid and Massively Parallel Incomplete Verifiers

Reference 52

Resolution: verified exact; arxiv_id, observed 2026-06-29T00:02:49.696269Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f8c872d7-2ad1-46b9-b9e6-8a5246b58005 · inbound

Tensor-Based Batch Fuzzing with Adaptive Perturbation Scaling for Deep Neural Networks cites this paper.

Tensor-Based Batch Fuzzing with Adaptive Perturbation Scaling for Deep Neural Networks Fast and Complete: Enabling Complete Neural Network Verification with Rapid and Massively Parallel Incomplete Verifiers

Reference 45

Resolution: verified exact; arxiv_id, observed 2026-06-25T22:38:32.943515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.