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Paper Citation Record · LEDGER

Synthetic Text Generation for Training Large Language Models via Gradient Matching

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2502.17607.

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

pith.paper-citation-record.v1
2502.17607 v2

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 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:59:03.031567Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T09:05:59.641157Z

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 5571f04f-54f5-4128-b128-4ada8f854d24 · inbound

Approximating Language Model Training Data from Weights cites this paper.

Approximating Language Model Training Data from Weights Synthetic Text Generation for Training Large Language Models via Gradient Matching

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-06T23:59:03.031567Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:59:03.031567Z digest=sha256:d3fc0182cbf014642e263da9f077eec7450c2290b2ed1524b7277c54b70fffcf

Observation 880fb956-0014-4305-acf6-984371291161 · inbound

Omnimodal Dataset Distillation via High-order Proxy Alignment cites this paper.

Omnimodal Dataset Distillation via High-order Proxy Alignment Synthetic Text Generation for Training Large Language Models via Gradient Matching

Reference 24

Resolution
verified exact
arxiv_id, observed 2026-05-11T09:05:59.643391Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-10T16:15:46.835576Z digest=sha256:a288d69e6d4c75e0fabf2212fb561c13353df2ddcbf2a7052ebf17aa96c6a394