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Paper Citation Record · LEDGER

Are Large-scale Soft Labels Necessary for Large-scale Dataset Distillation?

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2410.15919.

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

pith.paper-citation-record.v1
2410.15919 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 2026-08-06T21:31:59.073420Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T23:16:28.459032Z

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 a5c0af80-824d-4f89-8169-c1f96e232e7e · inbound

FADRM: Fast and Accurate Data Residual Matching for Dataset Distillation cites this paper.

FADRM: Fast and Accurate Data Residual Matching for Dataset Distillation Are Large-scale Soft Labels Necessary for Large-scale Dataset Distillation?

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-06T21:31:59.073420Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:31:59.073420Z digest=sha256:7ac93d5c3ac92066e8a19012bf6d2dc4508226e8c821f5911dcf31c95e611923

Observation bc1094ef-9afb-4b52-8b5e-0f792ddb4384 · inbound

DMGD: Train-Free Dataset Distillation with Semantic-Distribution Matching in Diffusion Models cites this paper.

DMGD: Train-Free Dataset Distillation with Semantic-Distribution Matching in Diffusion Models Are Large-scale Soft Labels Necessary for Large-scale Dataset Distillation?

Reference 70

Resolution
verified exact
arxiv_id, observed 2026-05-11T23:16:28.546505Z

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=2026-05-07T17:42:00.634333Z digest=sha256:58bf0bf300744b50e47fb4177c6765da9f1159840d940b9913226ef27a0026a7