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Paper Citation Record · LEDGER

Optimization without Backpropagation

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2209.06302.

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

pith.paper-citation-record.v1
2209.06302 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T13:47:52.970964Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T21:23:44.545109Z

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 8d026726-b8f0-4a24-9375-aa6ffde050fd · inbound

Noise-based Local Learning using Stochastic Magnetic Tunnel Junctions cites this paper.

Noise-based Local Learning using Stochastic Magnetic Tunnel Junctions Optimization without Backpropagation

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-11T13:47:52.970964Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:47:52.970964Z digest=sha256:1219caaa1165cc9be58c2e1083e8d4c14c2be6be1c0e487bf640c048ba72eea9

Observation 553782f1-621e-4dc0-9aab-f1cddcae824e · inbound

Warming Up for Zeroth-Order Federated Pre-Training with Low Resource Clients cites this paper.

Warming Up for Zeroth-Order Federated Pre-Training with Low Resource Clients Optimization without Backpropagation

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-05T10:59:56.170025Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:59:56.170025Z digest=sha256:2acd4988f9a43ec2196956ca08ffe3d5153f4868e3801789c323facb04bb65db

Observation 810a616f-d1f7-4ded-89ba-6af0529e498b · inbound

Position: Zeroth-Order Optimization in Deep Learning Is Underexplored, Not Underpowered cites this paper.

Position: Zeroth-Order Optimization in Deep Learning Is Underexplored, Not Underpowered Optimization without Backpropagation

Reference 60

Resolution
verified exact
arxiv_id, observed 2026-05-20T21:23:44.546444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-05-20T21:19:55.074853Z digest=sha256:1412ca255c73278738c6c63429157920fbad887a86225763ec6968c007ab1047