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Paper Citation Record · LEDGER

Adaptive Optimization for Enhanced Efficiency in Large-Scale Language Model Training

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2412.04718.

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

pith.paper-citation-record.v1
2412.04718 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T00:39:35.538864Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-10T23:26:40.111315Z

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 be00fb9f-d4c7-4821-a4ba-033bc2fa26ae · inbound

A Matrix Logic Approach to Efficient Frequent Itemset Discovery in Large Data Sets cites this paper.

A Matrix Logic Approach to Efficient Frequent Itemset Discovery in Large Data Sets Adaptive Optimization for Enhanced Efficiency in Large-Scale Language Model Training

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-11T00:39:35.538864Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:39:35.538864Z digest=sha256:adccfc16ebea62666721d8803eb214d77e697ab2f6c56f5325431c39a37ecc7e

Observation e157d387-c6be-41c3-8b4f-5dd55c3b5f52 · inbound

Deep Learning in Image Classification: Evaluating VGG19's Performance on Complex Visual Data cites this paper.

Deep Learning in Image Classification: Evaluating VGG19's Performance on Complex Visual Data Adaptive Optimization for Enhanced Efficiency in Large-Scale Language Model Training

Reference 8

Resolution
verified exact
local_arxiv, observed 2026-08-10T23:26:40.120866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T23:26:39.842984Z digest=sha256:36d7f9568a6565c9d8930ae965384b2e1c221223a6a06ec54314040c3b800c7f