Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Synthetic Data and Artificial Neural Networks for Natural Scene Text Recognition
As of 4 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:1406.2227.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-07-13T04:03:42.647632Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-07-04T15:59:57.294323Z
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 1f7cf046-c0cc-4f50-b9d7-e8633a696e1f · inbound
Improving Performance of End-to-End ASR on Numeric Sequences cites this paper.
Improving Performance of End-to-End ASR on Numeric Sequences Synthetic Data and Artificial Neural Networks for Natural Scene Text Recognition
Reference 14
- Resolution
- verified exact
- local_arxiv, observed 2026-05-25T11:30:42.374747Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 67daee99-50f3-44a6-bfda-57aa836edde2 · inbound
Fully Convolutional Networks for Handwriting Recognition cites this paper.
Fully Convolutional Networks for Handwriting Recognition Synthetic Data and Artificial Neural Networks for Natural Scene Text Recognition
Reference 16
- Resolution
- verified exact
- local_arxiv, observed 2026-05-24T23:36:27.630251Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 832dd062-43e2-4a3e-8719-fd40e63cd922 · inbound
GA-DAN: Geometry-Aware Domain Adaptation Network for Scene Text Detection and Recognition cites this paper.
GA-DAN: Geometry-Aware Domain Adaptation Network for Scene Text Detection and Recognition Synthetic Data and Artificial Neural Networks for Natural Scene Text Recognition
Reference 20
- Resolution
- verified exact
- local_arxiv, observed 2026-05-24T18:14:47.979136Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 4a360223-2b5e-4b2f-ba8f-c4ef9349bbb4 · inbound
GIT: A Generative Image-to-text Transformer for Vision and Language cites this paper.
GIT: A Generative Image-to-text Transformer for Vision and Language Synthetic Data and Artificial Neural Networks for Natural Scene Text Recognition
Reference 14
- Resolution
- verified exact
- local_arxiv, observed 2026-05-16T20:54:07.660142Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ba97096c-efc1-4c41-8a95-3535777299d9 · inbound
OCRBench: On the Hidden Mystery of OCR in Large Multimodal Models cites this paper.
OCRBench: On the Hidden Mystery of OCR in Large Multimodal Models Synthetic Data and Artificial Neural Networks for Natural Scene Text Recognition
Reference 112
- Resolution
- verified exact
- local_arxiv, observed 2026-05-17T09:55:35.593917Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation b4f50bba-5256-4d92-97fd-08fc3028644e · inbound
Document Parsing Unveiled: Techniques, Challenges, and Prospects for Structured Information Extraction cites this paper.
Document Parsing Unveiled: Techniques, Challenges, and Prospects for Structured Information Extraction Synthetic Data and Artificial Neural Networks for Natural Scene Text Recognition
Reference 92
- Resolution
- verified exact
- local_arxiv, observed 2026-05-23T19:15:47.244310Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation acc43485-507c-4e57-b207-32400130175f · inbound
Batch Loss Score for Dynamic Data Pruning cites this paper.
Batch Loss Score for Dynamic Data Pruning Synthetic Data and Artificial Neural Networks for Natural Scene Text Recognition
Reference 22
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T23:10:52.794138Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 96f846c7-77e6-4b65-bb60-0022351d66da · inbound
Advancing WordArt-Oriented Scene Text Recognition: Datasets and Methods cites this paper.
Advancing WordArt-Oriented Scene Text Recognition: Datasets and Methods Synthetic Data and Artificial Neural Networks for Natural Scene Text Recognition
Reference 23
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-04T15:59:57.295851Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 15421e78-1acf-4c63-bca9-915cabae0c8d · inbound
TextileNet: Towards Zero-shot Text-style Segmentation of Manuscripts cites this paper.
TextileNet: Towards Zero-shot Text-style Segmentation of Manuscripts Synthetic Data and Artificial Neural Networks for Natural Scene Text Recognition
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-07-13T04:03:42.647632Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.