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Paper Citation Record · LEDGER

AnySynth: Harnessing the Power of Image Synthetic Data Generation for Generalized Vision-Language Tasks

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2411.16749.

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

pith.paper-citation-record.v1
2411.16749 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 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-15T07:35:14.257562Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T07:39:50.478310Z

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 52e3cd3d-fc9b-450e-9da5-55576307077c · inbound

FoleyDirector: Fine-Grained Temporal Steering for Video-to-Audio Generation via Structured Scripts cites this paper.

FoleyDirector: Fine-Grained Temporal Steering for Video-to-Audio Generation via Structured Scripts AnySynth: Harnessing the Power of Image Synthetic Data Generation for Generalized Vision-Language Tasks

Reference 24

Resolution
verified exact
arxiv_id, observed 2026-05-15T07:39:50.480308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-15T07:35:14.257562Z digest=sha256:103e71b9f8f01bc8004afab18d3c20bd220154e5142adf8f46c77a7dfb05b2ad

Observation 01d80f55-4586-43b5-b625-b49aebed3ee0 · inbound

RefineAnything: Multimodal Region-Specific Refinement for Perfect Local Details cites this paper.

RefineAnything: Multimodal Region-Specific Refinement for Perfect Local Details AnySynth: Harnessing the Power of Image Synthetic Data Generation for Generalized Vision-Language Tasks

Reference 22

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T23:20:54.236052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T19:11:43.172296Z digest=sha256:14d50f8559904ed8d6f3dedc6b9ae24ea245d323eca6aa429a536114ef3038c6