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Paper Citation Record · LEDGER

A data-centric approach to class-specific bias in image data augmentation

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2403.04120.

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

pith.paper-citation-record.v1
2403.04120 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 2026-08-11T06:34:44.6726+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T11:18:29.843914Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-11T11:18:37.580450Z

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 0751aa38-db9f-4b68-8ac1-fd6eed36c4a2 · inbound

Error-driven Data-efficient Large Multimodal Model Tuning cites this paper.

Error-driven Data-efficient Large Multimodal Model Tuning A data-centric approach to class-specific bias in image data augmentation

Reference 4

Resolution
verified exact
local_arxiv, observed 2026-08-11T11:18:37.657401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-11T11:18:29.843914Z digest=sha256:d23ddc94c5653f3c3de40b672a06a71bb47bcd0af952981827209bd863ea5ea3

Observation aa6914c3-7c7c-4a84-adc4-3cfec520e9cd · inbound

Principled Synthetic Data Enables the First Scaling Laws for LLMs in Recommendation cites this paper.

Principled Synthetic Data Enables the First Scaling Laws for LLMs in Recommendation A data-centric approach to class-specific bias in image data augmentation

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-03T03:42:21.575446Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T03:42:21.575446Z digest=sha256:961a57dab043d22cdf8b9a38afb73d1c40cfd01ec8c9506ff8d28aacd39a2eae