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Paper Citation Record · LEDGER

A Survey on Data Augmentation in Large Model Era

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2401.15422.

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

pith.paper-citation-record.v1
2401.15422 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T11:09:59.339030Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T13:44:05.838907Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
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  • 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 5e57bc60-22c0-41a0-a997-f99f0e1504ea · inbound

Enhancing weed detection performance by means of GenAI-based image augmentation cites this paper.

Enhancing weed detection performance by means of GenAI-based image augmentation A Survey on Data Augmentation in Large Model Era

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-12T11:09:59.339030Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T11:09:59.339030Z digest=sha256:580d229ab2c1195d75aeb279e05f5f5c5918db0bb6c2300d419ba2e31ebf9186

Observation 683c34e4-8bab-4f00-b3c7-bd3a95c4646d · inbound

Seamless Optical Cloud Computing across Edge-Metro Network for Generative AI cites this paper.

Seamless Optical Cloud Computing across Edge-Metro Network for Generative AI A Survey on Data Augmentation in Large Model Era

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-11T22:41:21.064849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:41:21.064849Z digest=sha256:31dea954e37866b1171c89b95b1516feb3f03989271a0100bbe0673f5964eedb

Observation a3da62e0-00a3-44aa-baa4-780edad82762 · inbound

Synthetic Artifact Auditing: Tracing LLM-Generated Synthetic Data Usage in Downstream Applications cites this paper.

Synthetic Artifact Auditing: Tracing LLM-Generated Synthetic Data Usage in Downstream Applications A Survey on Data Augmentation in Large Model Era

Reference 100

Resolution
unresolved
no resolver link, observed 2026-08-09T17:43:55.886061Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T17:43:55.886061Z digest=sha256:2af5cf1bbbd9f8ff3026e2125f9238029abb0b540cdf3ae2dc47a6ba4409655c

Observation c9468b7b-d2fc-4ceb-ab17-0717c628f28d · inbound

Assessing Data Augmentation-Induced Bias in Training and Testing of Machine Learning Models cites this paper.

Assessing Data Augmentation-Induced Bias in Training and Testing of Machine Learning Models A Survey on Data Augmentation in Large Model Era

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-09T14:23:48.372305Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T14:23:48.372305Z digest=sha256:f56e0f82737de8e264539ff3f383d2742fec17b156ee237940ca2a379aa14f15

Observation 8b0c2260-b588-4876-b0f3-809ab39e684f · inbound

Evaluating Multimodal Large Language Models on Video Captioning via Monte Carlo Tree Search cites this paper.

Evaluating Multimodal Large Language Models on Video Captioning via Monte Carlo Tree Search A Survey on Data Augmentation in Large Model Era

Reference 2020

Resolution
unresolved
no resolver link, observed 2026-08-07T04:45:49.695413Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:45:49.695413Z digest=sha256:d647685855e475f68dbf62ba110cfc82de7669aeb514a21469603ee568289781

Observation 50c4f774-c729-4216-bf76-cfec8338833a · inbound

OAT-Rephrase: Optimization-Aware Training Data Rephrasing for Zeroth-Order LLM Fine-Tuning cites this paper.

OAT-Rephrase: Optimization-Aware Training Data Rephrasing for Zeroth-Order LLM Fine-Tuning A Survey on Data Augmentation in Large Model Era

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-07T05:16:55.294429Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:16:55.294429Z digest=sha256:cb8107d98309e924ef54189003c5c56275e0541323576c945054019e34267913

Observation e817f4fd-b0e4-4a2c-a0ea-14bcc2b182e0 · inbound

Debunk and Infer: Multimodal Fake News Detection via Diffusion-Generated Evidence and LLM Reasoning cites this paper.

Debunk and Infer: Multimodal Fake News Detection via Diffusion-Generated Evidence and LLM Reasoning A Survey on Data Augmentation in Large Model Era

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-07T04:51:45.152648Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:51:45.152648Z digest=sha256:3a5aa0a8648b9bd9fa166ec4889020bf34cc58fb267142606e6364a04f1136d9

Observation b72dd17f-f71d-452c-b1ea-419936c24593 · inbound

Separation Logic of Generic Resources via Sheafeology cites this paper.

Separation Logic of Generic Resources via Sheafeology A Survey on Data Augmentation in Large Model Era

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-06T05:22:31.230991Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:22:31.230991Z digest=sha256:d466613f4955a4eb248840413f1d90984b2377e69ead6715f519de8c3ffd1362

Observation 2b36fc04-15f1-4077-87df-8c694239d9a1 · inbound

Multi-turn Natural Language to Graph Query Language Translation cites this paper.

Multi-turn Natural Language to Graph Query Language Translation A Survey on Data Augmentation in Large Model Era

Reference 191

Resolution
unresolved
no resolver link, observed 2026-08-06T05:26:36.882364Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:26:36.882364Z digest=sha256:338f071d5832a75bd0093223cca13f811f988349dae220139c3f62b0fc7caa97

Observation 2b8f66be-2975-4537-9a49-eb57e77747b9 · inbound

NoiseCutMix: A Novel Data Augmentation Approach by Mixing Estimated Noise in Diffusion Models cites this paper.

NoiseCutMix: A Novel Data Augmentation Approach by Mixing Estimated Noise in Diffusion Models A Survey on Data Augmentation in Large Model Era

Reference 25

Resolution
verified exact
local_arxiv, observed 2026-08-05T13:44:05.995282Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-05T13:44:05.665777Z digest=sha256:91ad120f23146d4c1e02b5b3090e5a81029c87036325ff1a7783ae215936e8af

Observation 24ba1046-6faf-4b2f-b0aa-c1728ed0ed2c · inbound

Lost in Execution: On the Multilingual Robustness of Tool Calling in Large Language Models cites this paper.

Lost in Execution: On the Multilingual Robustness of Tool Calling in Large Language Models A Survey on Data Augmentation in Large Model Era

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-03T11:44:07.879360Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T11:44:07.879360Z digest=sha256:13942f31bf7deba4021fe58c49cb1611aebc4940bd6b3b4c8857846acf005c3b

Observation 959fb43f-695b-409b-86dc-cfc28dd6dab1 · inbound

A Six-Dimensional Taxonomy of Post-Training Adaptation Techniques with Applications in AI Governance cites this paper.

A Six-Dimensional Taxonomy of Post-Training Adaptation Techniques with Applications in AI Governance A Survey on Data Augmentation in Large Model Era

Reference 233

Resolution
unresolved
no resolver link, observed 2026-08-07T11:35:49.060799Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:35:49.060799Z digest=sha256:ae80798915ddc4b814f037de3daac45a32ebdc3dd9439259d7c3d466016ac6fe