Paper Citation Record · LEDGER

Identifying and attacking the saddle point problem in high-dimensional non-convex optimization

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:1406.2572.

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

pith.paper-citation-record.v1
1406.2572 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T18:53:28.643713Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-04T05:39:40.933683Z

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 da89cecc-aa20-4853-a341-a66eb210e258 · inbound

Don't Be So Positive: Negative Step Sizes in Second-Order Methods cites this paper.

Don't Be So Positive: Negative Step Sizes in Second-Order Methods Identifying and attacking the saddle point problem in high-dimensional non-convex optimization

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-12T18:53:28.643713Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6fccada1-7b2f-412a-a831-0046da041453 · inbound

Low Rank Based Subspace Inference for the Laplace Approximation of Bayesian Neural Networks cites this paper.

Low Rank Based Subspace Inference for the Laplace Approximation of Bayesian Neural Networks Identifying and attacking the saddle point problem in high-dimensional non-convex optimization

Reference 14

Resolution: metadata mismatch; local_arxiv, observed 2026-05-23T03:42:27.785071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3a2ac1b2-7b62-4483-afab-de8fe8c5a599 · inbound

Dimer-Enhanced Optimization: A First-Order Approach to Escaping Saddle Points in Neural Network Training cites this paper.

Dimer-Enhanced Optimization: A First-Order Approach to Escaping Saddle Points in Neural Network Training Identifying and attacking the saddle point problem in high-dimensional non-convex optimization

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T13:54:28.563026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3005f81b-d3da-47f7-962c-7470ea997c34 · inbound

Globally aware optimization with resurgence cites this paper.

Globally aware optimization with resurgence Identifying and attacking the saddle point problem in high-dimensional non-convex optimization

Reference 2014

Resolution: unresolved; no resolver link, observed 2026-08-05T12:46:30.585622Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a1416f7-d4e7-47b2-9b6f-db48eb364ab6 · inbound

An Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures cites this paper.

An Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures Identifying and attacking the saddle point problem in high-dimensional non-convex optimization

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-05T05:27:54.273487Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 28e869b9-887e-4231-ba0a-d6ad2d30c6e2 · inbound

Dimension-Free Saddle-Point Escape in Muon cites this paper.

Dimension-Free Saddle-Point Escape in Muon Identifying and attacking the saddle point problem in high-dimensional non-convex optimization

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-12T06:01:26.507724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 03abb548-8819-4c97-b686-004d12427186 · inbound

Shortcomings and capacities of real-constrained neural networks in complex spaces cites this paper.

Shortcomings and capacities of real-constrained neural networks in complex spaces Identifying and attacking the saddle point problem in high-dimensional non-convex optimization

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-07-02T07:36:44.740208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3349e146-f2ef-460f-ac56-6c395c20c493 · inbound

Statistical Properties of Training & Generalization cites this paper.

Statistical Properties of Training & Generalization Identifying and attacking the saddle point problem in high-dimensional non-convex optimization

Reference 57

Resolution: metadata mismatch; local_arxiv, observed 2026-07-04T05:39:40.935578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 30d164f3-521e-453a-9eaa-985cf8d15ca6 · inbound

Statistical Properties of Training & Generalization cites this paper.

Statistical Properties of Training & Generalization Identifying and attacking the saddle point problem in high-dimensional non-convex optimization

Reference 56

Resolution: metadata mismatch; local_arxiv, observed 2026-07-02T21:57:25.661252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 28548ba2-ad8d-465a-80ed-b0fadbf7becd · 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 Identifying and attacking the saddle point problem in high-dimensional non-convex optimization

Reference 57

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 37a78db8-545f-431d-8ec0-affc53cba368 · inbound

Landscape analysis for shallow neural networks: Complete classification of critical points for cubic activation and affine target functions cites this paper.

Landscape analysis for shallow neural networks: Complete classification of critical points for cubic activation and affine target functions Identifying and attacking the saddle point problem in high-dimensional non-convex optimization

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-02T00:02:19.445421Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.