Paper Citation Record · LEDGER

Synthetic Data Augmentation for Table Detection: Re-evaluating TableNet's Performance with Automatically Generated Document Images

As of 16 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2506.14583.

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

pith.paper-citation-record.v1
2506.14583 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T19:52:52.208340Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

34 of 34 outbound references displayed

verified exact1
verified fuzzy26
unresolved6
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c6125b64-f733-4935-83e7-ba48e9fd2a80 · outbound

This paper cites A survey on image data augmen- tation for deep learning,.

Synthetic Data Augmentation for Table Detection: Re-evaluating TableNet's Performance with Automatically Generated Document Images A survey on image data augmen- tation for deep learning,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:52:52.770992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation eed58065-6280-4655-b217-0087c5350a29 · outbound

This paper cites A survey on data augmentation for text classification,.

Synthetic Data Augmentation for Table Detection: Re-evaluating TableNet's Performance with Automatically Generated Document Images A survey on data augmentation for text classification,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:52:52.755669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation f870882c-8817-4a3e-91e1-45a1b4e0505b · outbound

This paper cites Synthesizing search engine queries from task-oriented user profiles,.

Synthetic Data Augmentation for Table Detection: Re-evaluating TableNet's Performance with Automatically Generated Document Images Synthesizing search engine queries from task-oriented user profiles,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:52:52.740483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation b41f6515-8f36-4728-a425-dcf66c904097 · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

Synthetic Data Augmentation for Table Detection: Re-evaluating TableNet's Performance with Automatically Generated Document Images Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 4

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Observation be698e3a-0e87-432f-b7d0-ad44ac1c9d65 · outbound

This paper cites A review of semantic segmentation using deep neural networks,.

Synthetic Data Augmentation for Table Detection: Re-evaluating TableNet's Performance with Automatically Generated Document Images A review of semantic segmentation using deep neural networks,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:52:52.724260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation d9ba705d-4e29-472f-baa0-9b93e71c72f3 · outbound

This paper cites Tablenet: Deep learning model for end-to-end table detection and tabular data extraction from scanned document images,.

Synthetic Data Augmentation for Table Detection: Re-evaluating TableNet's Performance with Automatically Generated Document Images Tablenet: Deep learning model for end-to-end table detection and tabular data extraction from scanned document images,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:52:52.707717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation c6f8d1fa-f2dc-4f0d-b61c-5d02513fa3db · outbound

This paper cites Recognition of tables and forms,.

Synthetic Data Augmentation for Table Detection: Re-evaluating TableNet's Performance with Automatically Generated Document Images Recognition of tables and forms,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:52:52.692495Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 6b1bd5fe-bf38-49ae-b296-8e70ff90d708 · outbound

This paper cites A survey of table recognition: Models, observations, transformations, and inferences,.

Synthetic Data Augmentation for Table Detection: Re-evaluating TableNet's Performance with Automatically Generated Document Images A survey of table recognition: Models, observations, transformations, and inferences,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:52:52.675590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 90e7be75-097a-4ed8-95a5-6eb88c0aa04e · outbound

This paper cites Design of an end-to-end method to extract information from tables,.

Synthetic Data Augmentation for Table Detection: Re-evaluating TableNet's Performance with Automatically Generated Document Images Design of an end-to-end method to extract information from tables,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:52:52.660391Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 3173d97e-7af9-4591-9adc-6cad66abfb5e · outbound

This paper cites On methods and tools of table detection, extraction and annotation in pdf documents,.

Synthetic Data Augmentation for Table Detection: Re-evaluating TableNet's Performance with Automatically Generated Document Images On methods and tools of table detection, extraction and annotation in pdf documents,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:52:52.644639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation bcde3b01-4f02-40b5-b140-9e70f462cf31 · outbound

This paper cites Table-processing paradigms: A research survey,.

Synthetic Data Augmentation for Table Detection: Re-evaluating TableNet's Performance with Automatically Generated Document Images Table-processing paradigms: A research survey,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:52:52.629150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 6774e757-5bd4-4101-8617-e89f22057c1a · outbound

This paper cites Tintin: A system for retrieval in text tables,.

Synthetic Data Augmentation for Table Detection: Re-evaluating TableNet's Performance with Automatically Generated Document Images Tintin: A system for retrieval in text tables,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:52:52.614374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation d0c57634-1676-42e3-8c02-778d59943c8b · outbound

This paper cites Trainable table location in document images,.

Synthetic Data Augmentation for Table Detection: Re-evaluating TableNet's Performance with Automatically Generated Document Images Trainable table location in document images,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:52:52.599691Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 51518067-c71b-4e21-ad28-92477988e6f0 · outbound

This paper cites Learning to detect tables in scanned document images using line information,.

Synthetic Data Augmentation for Table Detection: Re-evaluating TableNet's Performance with Automatically Generated Document Images Learning to detect tables in scanned document images using line information,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:52:52.585058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation a1348326-f712-46d0-acae-db83a8a206a7 · outbound

This paper cites Learning rich hidden markov models in document analysis: Table location,.

Synthetic Data Augmentation for Table Detection: Re-evaluating TableNet's Performance with Automatically Generated Document Images Learning rich hidden markov models in document analysis: Table location,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:52:52.569315Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 696dde4f-5f61-4bb5-97ab-3d24f95aa645 · outbound

This paper cites The t-recs table recognition and analysis system,.

Synthetic Data Augmentation for Table Detection: Re-evaluating TableNet's Performance with Automatically Generated Document Images The t-recs table recognition and analysis system,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:52:52.554417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 862fdc92-58ec-47eb-b8ac-8c3df00cd01b · outbound

This paper cites Table structure understand- ing and its performance evaluation,.

Synthetic Data Augmentation for Table Detection: Re-evaluating TableNet's Performance with Automatically Generated Document Images Table structure understand- ing and its performance evaluation,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:52:52.539666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation de9e6b8c-ada6-4834-b812-09d20f315909 · outbound

This paper cites Configurable table structure recognition in untagged pdf documents,.

Synthetic Data Augmentation for Table Detection: Re-evaluating TableNet's Performance with Automatically Generated Document Images Configurable table structure recognition in untagged pdf documents,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:52:52.524691Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 840c7e62-72c3-45cf-a3af-1686b8293241 · outbound

This paper cites A table detection method for pdf documents based on convolutional neural networks,.

Synthetic Data Augmentation for Table Detection: Re-evaluating TableNet's Performance with Automatically Generated Document Images A table detection method for pdf documents based on convolutional neural networks,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:52:52.509500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation aebec3d6-ad81-4aba-a470-fee4b61fd3d1 · outbound

This paper cites Table detection from document image using vertical arrangement of text blocks,.

Synthetic Data Augmentation for Table Detection: Re-evaluating TableNet's Performance with Automatically Generated Document Images Table detection from document image using vertical arrangement of text blocks,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:52:52.493276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 879215a4-1811-4482-b6b9-7830f3a4a29b · outbound

This paper cites Deepdesrt: Deep learning for detection and structure recognition of tables in document images,.

Synthetic Data Augmentation for Table Detection: Re-evaluating TableNet's Performance with Automatically Generated Document Images Deepdesrt: Deep learning for detection and structure recognition of tables in document images,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:52:52.478156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation e054c4c5-5d09-4bf6-9432-bd317825f624 · outbound

This paper cites A Saliency-based Convolutional Neural Network for Table and Chart Detection in Digitized Documents.

Synthetic Data Augmentation for Table Detection: Re-evaluating TableNet's Performance with Automatically Generated Document Images A Saliency-based Convolutional Neural Network for Table and Chart Detection in Digitized Documents

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-15T19:52:52.150558Z

Source-reported events for the cited work

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Observation 55c7be8f-baae-4b2a-beab-adfe88917a03 · outbound

This paper cites Learning table extraction from examples,.

Synthetic Data Augmentation for Table Detection: Re-evaluating TableNet's Performance with Automatically Generated Document Images Learning table extraction from examples,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:52:52.461848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 7a95094e-1d2a-4f09-a56d-a6056a03c128 · outbound

This paper cites Multidomain Document Layout Understanding using Few Shot Object Detection.

Synthetic Data Augmentation for Table Detection: Re-evaluating TableNet's Performance with Automatically Generated Document Images Multidomain Document Layout Understanding using Few Shot Object Detection

Reference 24

Resolution: verified exact; local_arxiv, observed 2026-08-15T19:52:52.336134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 7f05a663-498b-4a78-8638-720c6744c82c · outbound

This paper cites Supervised multi-specialist topic model with applications on large-scale electronic health record data.

Synthetic Data Augmentation for Table Detection: Re-evaluating TableNet's Performance with Automatically Generated Document Images Supervised multi-specialist topic model with applications on large-scale electronic health record data

Reference 25

Resolution: metadata mismatch; local_arxiv, observed 2026-08-15T19:52:52.313983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation aa045418-d073-43ba-874f-79e216fbce3b · outbound

This paper cites PubTables-1M: Towards comprehensive table extraction from unstructured documents.

Synthetic Data Augmentation for Table Detection: Re-evaluating TableNet's Performance with Automatically Generated Document Images PubTables-1M: Towards comprehensive table extraction from unstructured documents

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-15T19:52:52.169311Z

Source-reported events for the cited work

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Observation afc1923a-1d43-4a21-93a2-2df72c628626 · outbound

This paper cites DocBank: A Benchmark Dataset for Document Layout Analysis.

Synthetic Data Augmentation for Table Detection: Re-evaluating TableNet's Performance with Automatically Generated Document Images DocBank: A Benchmark Dataset for Document Layout Analysis

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-15T19:52:52.174110Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3c8b4d75-3162-4365-9084-11d31751f16f · outbound

This paper cites Table-transformer: A transformer-based model for table detection and structure recognition,.

Synthetic Data Augmentation for Table Detection: Re-evaluating TableNet's Performance with Automatically Generated Document Images Table-transformer: A transformer-based model for table detection and structure recognition,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:52:52.445542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 1c5b8bf2-9e3c-4406-a1a8-1b46f422a462 · outbound

This paper cites Tableformer: Robust transformer modeling for table-text encoding,.

Synthetic Data Augmentation for Table Detection: Re-evaluating TableNet's Performance with Automatically Generated Document Images Tableformer: Robust transformer modeling for table-text encoding,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:52:52.430015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 014bea0e-c5eb-4577-b325-968aa17732e8 · outbound

This paper cites Mask R-CNN.

Synthetic Data Augmentation for Table Detection: Re-evaluating TableNet's Performance with Automatically Generated Document Images Mask R-CNN

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-15T19:52:52.194458Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 31db0a3a-43e3-4e89-8c40-6af545105773 · outbound

This paper cites Marmot dataset.

Synthetic Data Augmentation for Table Detection: Re-evaluating TableNet's Performance with Automatically Generated Document Images Marmot dataset

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:52:52.414935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation e8417cbb-e0f5-46f6-afb9-b86cd1d3e348 · outbound

This paper cites Tensorflow,.

Synthetic Data Augmentation for Table Detection: Re-evaluating TableNet's Performance with Automatically Generated Document Images Tensorflow,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:52:52.399107Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 161d312e-3e47-4a80-9842-0be80f6d9c42 · outbound

This paper cites Tablenet enhancement,.

Synthetic Data Augmentation for Table Detection: Re-evaluating TableNet's Performance with Automatically Generated Document Images Tablenet enhancement,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:52:52.384343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 4f449286-002a-47b8-81c3-2408965cb78e · outbound

This paper cites TableFormer: Robust Transformer Modeling for Table-Text Encoding.

Synthetic Data Augmentation for Table Detection: Re-evaluating TableNet's Performance with Automatically Generated Document Images TableFormer: Robust Transformer Modeling for Table-Text Encoding

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-15T19:52:52.188564Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.