Paper Citation Record · LEDGER

Training on Thin Air: Improve Image Classification with Generated Data

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2305.15316.

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

pith.paper-citation-record.v1
2305.15316 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 2026-08-20T06:33:59.587034+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:53:05.020228Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T18:13:49.197094Z

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 2d60cad3-02ee-4c8a-8027-3785f74936ed · inbound

Merging synthetic and real embryo data for advanced AI predictions cites this paper.

Merging synthetic and real embryo data for advanced AI predictions Training on Thin Air: Improve Image Classification with Generated Data

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-12T04:36:18.132667Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 21e7e409-784b-49de-bdb8-67885969d935 · inbound

Generative Data Mining with Longtail-Guided Diffusion cites this paper.

Generative Data Mining with Longtail-Guided Diffusion Training on Thin Air: Improve Image Classification with Generated Data

Reference 103

Resolution: unresolved; no resolver link, observed 2026-08-09T13:53:04.741765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f060881f-da87-4c79-b29d-4d91993eb39b · inbound

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

LoFT: LoRA-fused Training Dataset Generation with Few-shot Guidance Training on Thin Air: Improve Image Classification with Generated Data

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-15T20:53:05.020228Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f61543f-5d64-42ca-b214-283fe58ade9e · inbound

SoK: Can Synthetic Images Replace Real Data? A Survey of Utility and Privacy of Synthetic Image Generation cites this paper.

SoK: Can Synthetic Images Replace Real Data? A Survey of Utility and Privacy of Synthetic Image Generation Training on Thin Air: Improve Image Classification with Generated Data

Reference 134

Resolution: unresolved; no resolver link, observed 2026-08-06T23:12:17.288618Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 97141dff-f77c-4606-9e25-ab8659dd7663 · 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 Training on Thin Air: Improve Image Classification with Generated Data

Reference 62

Resolution: malformed identifier; no resolver link, observed 2026-08-06T20:04:07.964738Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6597f7c7-69b2-4c23-9601-faae8d198671 · inbound

Beyond Objects: Contextual Synthetic Data Generation for Fine-Grained Classification cites this paper.

Beyond Objects: Contextual Synthetic Data Generation for Fine-Grained Classification Training on Thin Air: Improve Image Classification with Generated Data

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-04T07:54:53.089720Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e16e1959-7d92-441e-a0ad-db8fb24aee7b · inbound

Towards Controllable Image Generation through Representation-Conditioned Diffusion Models cites this paper.

Towards Controllable Image Generation through Representation-Conditioned Diffusion Models Training on Thin Air: Improve Image Classification with Generated Data

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-06-29T18:13:49.198648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 64a7a392-e6e5-4735-a384-1e2a5a38a417 · inbound

Post-Generation Curation of Synthetic Images via Homogeneous-Heterogeneous Splitting cites this paper.

Post-Generation Curation of Synthetic Images via Homogeneous-Heterogeneous Splitting Training on Thin Air: Improve Image Classification with Generated Data

Reference 25

Resolution: unresolved; no resolver link, observed 2026-07-12T08:12:18.373103Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.