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Paper Citation Record · LEDGER

DreamDA: Generative Data Augmentation with Diffusion Models

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2403.12803.

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

pith.paper-citation-record.v1
2403.12803 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T18:18:12.906066Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T15:48:34.988160Z

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 b7528a40-c6e9-497a-afc6-3461d561194a · inbound

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation cites this paper.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation DreamDA: Generative Data Augmentation with Diffusion Models

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-11T18:18:12.906066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:18:12.906066Z digest=sha256:bb8bbb01a16f3a9a7d04a7347d3d75a53a31965c5c95966da20008920e26fefc

Observation ed2a13f1-21cb-4cd4-986c-1a86d8f8034c · inbound

Canonical Latent Representations in Conditional Diffusion Models cites this paper.

Canonical Latent Representations in Conditional Diffusion Models DreamDA: Generative Data Augmentation with Diffusion Models

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-07T04:43:05.889147Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:43:05.889147Z digest=sha256:cd5aa1655a739602b89cf3350ebeb1ddd8ce32a40bbe1dcb965d57a42643e887

Observation 7da76288-af32-4b69-94cc-25cd4cfb5711 · inbound

Generate, Refine, and Encode: Leveraging Synthesized Novel Samples for On-the-Fly Fine-Grained Category Discovery cites this paper.

Generate, Refine, and Encode: Leveraging Synthesized Novel Samples for On-the-Fly Fine-Grained Category Discovery DreamDA: Generative Data Augmentation with Diffusion Models

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-06T20:04:01.041276Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:04:01.041276Z digest=sha256:deadc1b0b7107db17cae7197e17c12ab8c21252f0d5419bf8f58757067af33b3

Observation 27a195f4-6d36-479a-919c-7059df08b1c2 · inbound

RulerNet: Learning Perspective-Invariant Ruler Representations for Robust Image Scale Estimation cites this paper.

RulerNet: Learning Perspective-Invariant Ruler Representations for Robust Image Scale Estimation DreamDA: Generative Data Augmentation with Diffusion Models

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-06T18:53:50.207116Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:53:50.207116Z digest=sha256:33235b360b939b5eab1f15c4147d44a84384f8faa315ed84eb29fdd14c3a619d

Observation a7db638e-5655-47ed-93f5-21ecfe2973e0 · inbound

Decomposing Subject-Driven Image Generation via Intermediate Structural Prediction cites this paper.

Decomposing Subject-Driven Image Generation via Intermediate Structural Prediction DreamDA: Generative Data Augmentation with Diffusion Models

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-05-21T05:33:58.701787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-21T05:30:59.903879Z digest=sha256:8d2328a98a16db9e57e178254b752dd9f7f89c56c0b337c4657302de2facfaf8

Observation a2524e47-7bb1-46b8-a79b-efbaf913d51a · inbound

Decomposing Subject-Driven Image Generation via Intermediate Structural Prediction cites this paper.

Decomposing Subject-Driven Image Generation via Intermediate Structural Prediction DreamDA: Generative Data Augmentation with Diffusion Models

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-02T13:34:20.924761Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T13:34:20.924761Z digest=sha256:321ee0950740fab80134c444688dc886d0d73d1114876faa26e19ce8396c7f7b

Observation a7383711-41c3-4dc1-a4d2-f2196ae48ac2 · inbound

FlowCIR: Semantic Transport via Flow Matching for Zero-Shot Composed Image Retrieval cites this paper.

FlowCIR: Semantic Transport via Flow Matching for Zero-Shot Composed Image Retrieval DreamDA: Generative Data Augmentation with Diffusion Models

Reference 15

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T15:48:34.989630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-03T15:41:05.166452Z digest=sha256:d71b55d53397b9a6eb3b8fefb057c5c1afb4899b4b9d7a97bea8dfa79ba260ea

Observation 3c015f2b-ba95-4035-8b2b-2717be0a6883 · inbound

Layering Virtual Try-On cites this paper.

Layering Virtual Try-On DreamDA: Generative Data Augmentation with Diffusion Models

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-01T04:11:50.024884Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T04:11:50.024884Z digest=sha256:9fca83cbabc5f8d400b0e5a2bbfafdc7b1c01648f4998b2ebdb970b7d514ed36