Paper Citation Record · LEDGER

Provable Benefit of Orthogonal Initialization in Optimizing Deep Linear Networks

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2001.05992.

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

pith.paper-citation-record.v1
2001.05992 v1

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 2026-08-12T06:34:41.77262+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T19:03:05.950965Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T08:26:48.332888Z

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 c4dc4454-b080-48c2-841b-862391a3a133 · inbound

Parseval Regularization for Continual Reinforcement Learning cites this paper.

Parseval Regularization for Continual Reinforcement Learning Provable Benefit of Orthogonal Initialization in Optimizing Deep Linear Networks

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-11T19:03:05.950965Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c7cb8ed0-30e0-4fa7-bfa7-dfd1982fb8ac · inbound

Criticality and Saturation in Orthogonal Neural Networks cites this paper.

Criticality and Saturation in Orthogonal Neural Networks Provable Benefit of Orthogonal Initialization in Optimizing Deep Linear Networks

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-11T19:16:08.949902Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 9d24d62d-6b0e-4b38-aefc-4093c9f8710e · inbound

When Evidence is Sparse: Weakly Supervised Early Failure Alerting in Dialogs and LLM-Agent Trajectories cites this paper.

When Evidence is Sparse: Weakly Supervised Early Failure Alerting in Dialogs and LLM-Agent Trajectories Provable Benefit of Orthogonal Initialization in Optimizing Deep Linear Networks

Reference 1

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T08:26:48.334470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 3be03867-1dcd-4b4b-b175-9ed5c57cb53a · inbound

PLATO: Pointer Learner for Agent and Task Openness cites this paper.

PLATO: Pointer Learner for Agent and Task Openness Provable Benefit of Orthogonal Initialization in Optimizing Deep Linear Networks

Reference 49

Resolution: unresolved; no resolver link, observed 2026-07-31T01:53:02.332328Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.