Pith. sign in

Paper Citation Record · LEDGER

Provable defenses against adversarial examples via the convex outer adversarial polytope

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:1711.00851.

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

pith.paper-citation-record.v1
1711.00851 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 2026-08-14T06:32:32.682623+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T13:26:18.889492Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-14T10:36:30.152877Z

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 0708b955-1191-4ee4-903a-78256777ef12 · inbound

A Survey of Recent Scalability Improvements for Semidefinite Programming with Applications in Machine Learning, Control, and Robotics cites this paper.

A Survey of Recent Scalability Improvements for Semidefinite Programming with Applications in Machine Learning, Control, and Robotics Provable defenses against adversarial examples via the convex outer adversarial polytope

Reference 119

Resolution
unresolved
no resolver link, observed 2026-08-14T13:26:18.889492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T13:26:18.889492Z digest=sha256:15ff2d6677e8c6f6df6acf006359440b165923709c62b0dc34be3947887e2472

Observation 401599df-741a-4589-ad55-a9cc7e0c3fcc · inbound

Adversarial shape perturbations on 3D point clouds cites this paper.

Adversarial shape perturbations on 3D point clouds Provable defenses against adversarial examples via the convex outer adversarial polytope

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-14T13:01:55.848357Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T13:01:55.848357Z digest=sha256:3d6fc5b66077e2e4c6827c6e29d918302040cc7629061807706bbffc97e98eed

Observation c0667f11-d054-48be-bdc2-f61aeffde05d · inbound

Implicit Deep Learning cites this paper.

Implicit Deep Learning Provable defenses against adversarial examples via the convex outer adversarial polytope

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-14T12:56:19.065180Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T12:56:19.065180Z digest=sha256:451bcf0f7f2f7f80a08934535395c1c54494e025e64c41e078cc0961651dee3d

Observation 3644161d-0523-4d5f-a896-a09856efe9e0 · inbound

Deep Learning Theory Review: An Optimal Control and Dynamical Systems Perspective cites this paper.

Deep Learning Theory Review: An Optimal Control and Dynamical Systems Perspective Provable defenses against adversarial examples via the convex outer adversarial polytope

Reference 101

Resolution
verified exact
local_arxiv, observed 2026-08-14T10:36:30.161583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-14T10:36:30.042214Z digest=sha256:7eeada1ae0482eaa2acfc7c69965d8bee8d75fecdb75e3944088da9614ef2057

Observation 64b2b158-4a41-4e23-91b7-97599cc1369d · inbound

When cheap gradients fail: the measurement cost of attacking quantum classifiers cites this paper.

When cheap gradients fail: the measurement cost of attacking quantum classifiers Provable defenses against adversarial examples via the convex outer adversarial polytope

Reference 28

Resolution
unresolved
no resolver link, observed 2026-07-14T07:06:53.439022Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T07:06:53.439022Z digest=sha256:4d152ea0bbc220500e0c06c20950a4c8dcee88ed74ebb72c2d9942984ad8ee6f