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Paper Citation Record · LEDGER

Fill-Up: Balancing Long-Tailed Data with Generative Models

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2306.07200.

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

pith.paper-citation-record.v1
2306.07200 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:22:05.939026Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T18:41:28.843725Z

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 ae0ff7df-d82a-492b-8372-3ed59e906753 · inbound

Boosting Statistic Learning with Synthetic Data from Pretrained Large Models cites this paper.

Boosting Statistic Learning with Synthetic Data from Pretrained Large Models Fill-Up: Balancing Long-Tailed Data with Generative Models

Reference 87

Resolution
unresolved
no resolver link, observed 2026-08-15T23:22:05.939026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:22:05.939026Z digest=sha256:0d364fc5bf57d3097da8c059c8b986177cfb489fd63e45c19fb329403e5a2030

Observation cababd4a-882d-45c4-98fe-c28f827eaef7 · inbound

LoFT: LoRA-fused Training Dataset Generation with Few-shot Guidance cites this paper.

LoFT: LoRA-fused Training Dataset Generation with Few-shot Guidance Fill-Up: Balancing Long-Tailed Data with Generative Models

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-15T20:53:04.948108Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:53:04.948108Z digest=sha256:b215051ae4fac94f303cf3074e0fdd4ff3512c091f1caf9bf6b2580ba1088320

Observation f32aa554-b130-40c8-8a98-fa39c508156b · inbound

Improving Text-to-Image Generation with Intrinsic Self-Confidence Rewards cites this paper.

Improving Text-to-Image Generation with Intrinsic Self-Confidence Rewards Fill-Up: Balancing Long-Tailed Data with Generative Models

Reference 64

Resolution
verified exact
arxiv_id, observed 2026-05-15T18:41:28.847254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-15T18:40:18.940889Z digest=sha256:e383809ddb4fa69f5836ceeb2982674fe45d31ee65d5a2f12c32e44ad0b0b4b9