Paper Citation Record · LEDGER

Learning Associative Memories with Gradient Descent

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2402.18724.

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

pith.paper-citation-record.v1
2402.18724 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T15:06:30.627196Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T23:10:44.877031Z

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 cf83075d-3f7d-41a7-b93c-ec3785888d09 · inbound

Rethinking Associative Memory Mechanism in Induction Head cites this paper.

Rethinking Associative Memory Mechanism in Induction Head Learning Associative Memories with Gradient Descent

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T15:06:30.627196Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 94ed4ca1-0948-41bf-b368-c8583e1764af · inbound

The Features at Convergence Theorem: a first-principles alternative to the Neural Feature Ansatz for how networks learn representations cites this paper.

The Features at Convergence Theorem: a first-principles alternative to the Neural Feature Ansatz for how networks learn representations Learning Associative Memories with Gradient Descent

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T19:31:19.335976Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 062bd6b0-43a0-4f38-a1a9-a41b7d86e4b3 · inbound

Provable Knowledge Acquisition and Extraction in One-Layer Transformers cites this paper.

Provable Knowledge Acquisition and Extraction in One-Layer Transformers Learning Associative Memories with Gradient Descent

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-21T23:10:44.879130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 1a821803-33f0-4938-b335-5d808fe7bdf2 · inbound

Unveiling the Mechanisms of Multi-Hop Reasoning in Transformers via Identity Bridge cites this paper.

Unveiling the Mechanisms of Multi-Hop Reasoning in Transformers via Identity Bridge Learning Associative Memories with Gradient Descent

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-04T13:54:13.607091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation df025c8f-189a-4a3d-852b-81933854eabe · inbound

Muon in Associative Memory Learning: Training Dynamics and Scaling Laws cites this paper.

Muon in Associative Memory Learning: Training Dynamics and Scaling Laws Learning Associative Memories with Gradient Descent

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-03T04:14:13.514558Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 64cd932e-b9f1-48c3-b178-762813e8b388 · inbound

Sharp Capacity Thresholds in Linear Associative Memory: From Top-1 Retrieval to Tail-Average Learning cites this paper.

Sharp Capacity Thresholds in Linear Associative Memory: From Top-1 Retrieval to Tail-Average Learning Learning Associative Memories with Gradient Descent

Reference 47

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T18:16:10.107695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.