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Paper Citation Record · LEDGER

Data Augmentation using Pre-trained Transformer Models

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2003.02245.

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

pith.paper-citation-record.v1
2003.02245 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:06:00.829204Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T03:59:32.561073Z

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 2700f9ff-9dbd-45e6-8974-ed11bc78d357 · inbound

Explainable AI: XAI-Guided Context-Aware Data Augmentation cites this paper.

Explainable AI: XAI-Guided Context-Aware Data Augmentation Data Augmentation using Pre-trained Transformer Models

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-07T11:06:00.829204Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:06:00.829204Z digest=sha256:7cd56f812afa87b7bbf4f361181afb07394d5a31f6402d7a777e300c54c2939f

Observation cce13c21-8654-489a-9be0-7db2f5efa282 · inbound

The Synthetic Mirror -- Synthetic Data at the Age of Agentic AI cites this paper.

The Synthetic Mirror -- Synthetic Data at the Age of Agentic AI Data Augmentation using Pre-trained Transformer Models

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T00:47:36.509825Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:47:36.509825Z digest=sha256:435e4a594d6855fdcd61067b40e41acd0f0c023756186ddc30b5891943a1745c

Observation 6cadf598-dd68-40d4-bb56-7574ed5b8e38 · inbound

Backtranslation and paraphrasing in the LLM era? Comparing data augmentation methods for emotion classification cites this paper.

Backtranslation and paraphrasing in the LLM era? Comparing data augmentation methods for emotion classification Data Augmentation using Pre-trained Transformer Models

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-06T15:55:22.724420Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:55:22.724420Z digest=sha256:da810959f4e98b6dbdf64a090997f327b249c1fa1ec8b366c3def32aa558bbcf

Observation f2ac3ecc-758b-4300-957d-b8e267b5ff16 · inbound

Assisted Counterspeech Writing at the Crossroads of Hate Speech and Misinformation cites this paper.

Assisted Counterspeech Writing at the Crossroads of Hate Speech and Misinformation Data Augmentation using Pre-trained Transformer Models

Reference 280

Resolution
verified exact
arxiv_id, observed 2026-05-22T07:11:12.996569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-22T07:07:36.726431Z digest=sha256:dafe562e9c663b87670c9be3ca8f30ba73ca39a4c373bb86cb10467d5ba6be42

Observation 82180552-d931-4dd1-8959-e97e599526b0 · inbound

CATCH-ME if you RAG: a dataset of Contextually Annotated multi-Turn Counterspeech against Hate and Misinformation Exchanges cites this paper.

CATCH-ME if you RAG: a dataset of Contextually Annotated multi-Turn Counterspeech against Hate and Misinformation Exchanges Data Augmentation using Pre-trained Transformer Models

Reference 290

Resolution
verified exact
arxiv_id, observed 2026-07-04T03:59:32.563276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-26T17:30:07.053955Z digest=sha256:5e52bdbac7f58707276ebe92ef3933fcd77d499d735ea342d2512411ff2369fb