Paper Citation Record · LEDGER

Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Complete and Incomplete Neural Network Robustness Verification

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2103.06624.

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

pith.paper-citation-record.v1
2103.06624 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 2026-08-09T06:31:02.800959+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:55:08.346813Z

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

13
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 43fb3c35-88de-4595-8a80-51e73896ffc0 · inbound

Efficient Certified Reasoning for Binarized Neural Networks cites this paper.

Efficient Certified Reasoning for Binarized Neural Networks Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Complete and Incomplete Neural Network Robustness Verification

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-06T22:55:08.346813Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4f4827b1-be76-4440-b60d-d63b8dc3317c · inbound

Glitches in Decision Tree Ensemble Models cites this paper.

Glitches in Decision Tree Ensemble Models Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Complete and Incomplete Neural Network Robustness Verification

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-06T16:16:29.718627Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cf67916c-72ba-4f89-847c-4e87ed84836f · inbound

Adversarial Examples Are Not Bugs, They Are Superposition cites this paper.

Adversarial Examples Are Not Bugs, They Are Superposition Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Complete and Incomplete Neural Network Robustness Verification

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-05T16:56:11.805323Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 583ef8fc-4b3f-4ae2-9f81-88895e271d9e · inbound

IoUCert: Robustness Verification for Anchor-based Object Detectors cites this paper.

IoUCert: Robustness Verification for Anchor-based Object Detectors Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Complete and Incomplete Neural Network Robustness Verification

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-02T19:17:08.753187Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d56c3d69-9a3c-43fd-819a-a3f3486d85d2 · inbound

Lipschitz-Based Robustness Certification Under Floating-Point Execution cites this paper.

Lipschitz-Based Robustness Certification Under Floating-Point Execution Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Complete and Incomplete Neural Network Robustness Verification

Reference 46

Resolution: unresolved; no resolver link, observed 2026-07-15T14:07:56.936206Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9b471d62-434c-458d-8292-6dcf78fd9efb · inbound

Lipschitz-Based Robustness Certification Under Floating-Point Execution cites this paper.

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-02T18:47:59.469696Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f35db220-a4eb-42de-b25e-5324593f2002 · inbound

Adversarial Robustness of Time-Series Classification for Crystal Collimator Alignment cites this paper.

Adversarial Robustness of Time-Series Classification for Crystal Collimator Alignment Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Complete and Incomplete Neural Network Robustness Verification

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-10T19:50:45.551562Z

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.

Observation 3bf1a8e9-72f5-42bd-bbf3-d7bff1d04e7e · inbound

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

Quantitative Linear Logic for Neuro-Symbolic Learning and Verification Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Complete and Incomplete Neural Network Robustness Verification

Reference 124

Resolution: verified exact; arxiv_id, observed 2026-05-14T17:32:30.387930Z

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.

Observation 7cda1b94-f3b6-423f-a908-77f783d2accb · inbound

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

Reference 124

Resolution: verified exact; arxiv_id, observed 2026-05-15T05:45:05.072638Z

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.

Observation bdd464b2-7033-4986-8ed9-77a57806aaf4 · inbound

Scaling Neural Network Verification with Tensor Parallelism and Fully Sharded Data Parallelism cites this paper.

Scaling Neural Network Verification with Tensor Parallelism and Fully Sharded Data Parallelism Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Complete and Incomplete Neural Network Robustness Verification

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-07-03T00:17:29.226247Z

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.