Paper Citation Record · LEDGER

Data Boost: Text Data Augmentation Through Reinforcement Learning Guided Conditional Generation

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2012.02952.

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

pith.paper-citation-record.v1
2012.02952 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:36:02.190319Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T15:55:22.837812Z

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 1992859e-50b2-4710-8b02-7625d139f00d · inbound

MapExplorer: New Content Generation from Low-Dimensional Visualizations cites this paper.

MapExplorer: New Content Generation from Low-Dimensional Visualizations Data Boost: Text Data Augmentation Through Reinforcement Learning Guided Conditional Generation

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-11T04:39:40.750620Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 696c9fd8-af7c-42a3-bc2c-0a960a60bcf1 · inbound

The Synthetic Imputation Approach: Generating Optimal Synthetic Texts For Underrepresented Categories In Supervised Classification Tasks cites this paper.

The Synthetic Imputation Approach: Generating Optimal Synthetic Texts For Underrepresented Categories In Supervised Classification Tasks Data Boost: Text Data Augmentation Through Reinforcement Learning Guided Conditional Generation

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-16T11:36:02.190319Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bb868db3-d52c-4e5f-86e8-b908eb5c61b3 · 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 Boost: Text Data Augmentation Through Reinforcement Learning Guided Conditional Generation

Reference 22

Resolution: metadata mismatch; local_arxiv, observed 2026-08-06T15:55:22.840783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e31e4056-8c47-4bae-8153-c57aa53bb075 · inbound

Layering Virtual Try-On cites this paper.

Layering Virtual Try-On Data Boost: Text Data Augmentation Through Reinforcement Learning Guided Conditional Generation

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-01T04:11:50.076633Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.