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Paper Citation Record · LEDGER

On Training Data Influence of GPT Models

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2404.07840.

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

pith.paper-citation-record.v1
2404.07840 v3

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 2026-08-09T22:08:48.421948Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T04:37:09.595224Z

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 4aab51a0-159a-40e5-a4ca-1f1588fd8751 · inbound

Towards Unified Attribution in Explainable AI, Data-Centric AI, and Mechanistic Interpretability cites this paper.

Towards Unified Attribution in Explainable AI, Data-Centric AI, and Mechanistic Interpretability On Training Data Influence of GPT Models

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-09T22:08:48.421948Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T22:08:48.421948Z digest=sha256:0d422247efdb3f6725523cb3824fcb9a030a77bc018df2f5d6ebcf36c1ad0021

Observation c11286b3-e458-449a-8a2d-2bc6af9b4751 · inbound

ClusterUCB: Efficient Gradient-Based Data Selection for Targeted Fine-Tuning of LLMs cites this paper.

ClusterUCB: Efficient Gradient-Based Data Selection for Targeted Fine-Tuning of LLMs On Training Data Influence of GPT Models

Reference 24

Resolution
verified exact
local_arxiv, observed 2026-08-07T04:37:09.688569Z

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=arxiv_source observed=2026-08-07T04:37:07.755069Z digest=sha256:c13bb57b0f6e1aadcd1a94e44322ceb35913c8c7d5b0d5c3eb97a93b6a5ad3f9