Paper Citation Record · LEDGER

A Survey on Efficient Training of Transformers

As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2302.01107.

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

pith.paper-citation-record.v1
2302.01107 v3

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 2026-08-06T06:34:29.942622+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-09T22:53:25.139723Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-09T22:56:37.663046Z

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 edcf80ad-c789-40ce-8aa4-fdcaec5d6cdf · inbound

Agentic Physical AI toward a Domain-Specific Foundation Model for Nuclear Reactor Control cites this paper.

Agentic Physical AI toward a Domain-Specific Foundation Model for Nuclear Reactor Control A Survey on Efficient Training of Transformers

Reference 47

Resolution: verified exact; arxiv_id, observed 2026-05-21T17:00:24.071241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 43005694-6346-4883-aa13-c0f984cc85e8 · inbound

Navigating LLM Valley: From AdamW to Memory-Efficient and Matrix-Based Optimizers cites this paper.

Navigating LLM Valley: From AdamW to Memory-Efficient and Matrix-Based Optimizers A Survey on Efficient Training of Transformers

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-05-12T06:41:45.468353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 70b8335c-5139-40c9-9a90-6f78cb5790d7 · inbound

Improving End-to-End Speech Recognition for Dysarthric Speech through In-Domain Data Augmentation cites this paper.

Improving End-to-End Speech Recognition for Dysarthric Speech through In-Domain Data Augmentation A Survey on Efficient Training of Transformers

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-07-04T05:19:34.964305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 938a09f6-fabf-4a49-9073-56075b1f2ec3 · inbound

Imputation Meets Clustering: Exploiting Latent Subgroup Structure for Missing Data Recovery cites this paper.

Imputation Meets Clustering: Exploiting Latent Subgroup Structure for Missing Data Recovery A Survey on Efficient Training of Transformers

Reference 50

Resolution: metadata mismatch; local_arxiv, observed 2026-07-09T22:56:37.664326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.