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Paper Citation Record · LEDGER

PaCoNet: Deep Data Extraction for Parallel Coordinates

As of 9 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2608.06030.

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

pith.paper-citation-record.v1
2608.06030 v1

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T19:07:15.240317Z

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

37 of 37 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c34af8df-2ffa-4b23-9d59-67bb72af8981 · outbound

This paper cites In: Visualization and Data Analysis 2010 (2010).

PaCoNet: Deep Data Extraction for Parallel Coordinates In: Visualization and Data Analysis 2010 (2010)

Reference 1

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Observation 150d4437-8f50-49fb-bea2-8c93d98fc640 · outbound

This paper cites In: 2012 IEEE 12th International Conference on Bioinformatics & Bioengineering (BIBE) (2012).

PaCoNet: Deep Data Extraction for Parallel Coordinates In: 2012 IEEE 12th International Conference on Bioinformatics & Bioengineering (BIBE) (2012)

Reference 2

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Observation d8905638-319f-48e8-b1e8-42a1cb187115 · outbound

This paper cites IEEE Transactions on Visualization and Computer Graphics (2024).

PaCoNet: Deep Data Extraction for Parallel Coordinates IEEE Transactions on Visualization and Computer Graphics (2024)

Reference 3

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Observation 37988e32-ca88-4716-b272-e338995ce9de · outbound

This paper cites In: International Conference on Pattern Recognition (2024).

PaCoNet: Deep Data Extraction for Parallel Coordinates In: International Conference on Pattern Recognition (2024)

Reference 4

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Observation 1851074d-d129-4d84-9098-0da090fa3c2c · outbound

This paper cites In: Proceedings of KDD-96.

PaCoNet: Deep Data Extraction for Parallel Coordinates In: Proceedings of KDD-96

Reference 5

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Observation 005e3a40-8bc3-4b9e-b8bd-07d9a537db1f · outbound

This paper cites In: Proceedings on Seventh International Conference on Information Visualization, 2003 (2003).

PaCoNet: Deep Data Extraction for Parallel Coordinates In: Proceedings on Seventh International Conference on Information Visualization, 2003 (2003)

Reference 6

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Observation 6b0f322d-566f-48e7-badb-62bea9640de4 · outbound

This paper cites IEEE Transactions on Pattern Analysis and Machine Intelligence (2020), https://api.semanticscholar.org/CorpusID:212644678.

PaCoNet: Deep Data Extraction for Parallel Coordinates IEEE Transactions on Pattern Analysis and Machine Intelligence (2020), https://api.semanticscholar.org/CorpusID:212644678

Reference 7

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Observation b77e2778-ffa7-45bc-844b-d75c9511eee5 · outbound

This paper cites In: 34th Annual Conference of the European Association for Computer Graphics, Eurographics 2013 - State of the Art Reports.

PaCoNet: Deep Data Extraction for Parallel Coordinates In: 34th Annual Conference of the European Association for Computer Graphics, Eurographics 2013 - State of the Art Reports

Reference 8

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Observation b6ff8bb4-12a6-4f08-aa06-1f04d1afea70 · outbound

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PaCoNet: Deep Data Extraction for Parallel Coordinates Unresolved cited work

Reference 9

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Observation 96613158-789b-4442-bae1-677f582388ba · outbound

This paper cites The Visual Computer (1985).

PaCoNet: Deep Data Extraction for Parallel Coordinates The Visual Computer (1985)

Reference 10

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Observation 7c9a5129-d89f-4a23-9a87-f67d597d6b5b · outbound

This paper cites In: Proceedings of WACV (2022).

PaCoNet: Deep Data Extraction for Parallel Coordinates In: Proceedings of WACV (2022)

Reference 11

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This paper cites In: 54th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference (2013).

PaCoNet: Deep Data Extraction for Parallel Coordinates In: 54th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference (2013)

Reference 12

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Observation caac607a-1cf8-4985-8e18-195a45f4437d · outbound

This paper cites LineFormer: Rethinking Line Chart Data Extraction as Instance Segmentation.

PaCoNet: Deep Data Extraction for Parallel Coordinates LineFormer: Rethinking Line Chart Data Extraction as Instance Segmentation

Reference 13

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Observation e03185ae-fef6-4ab3-a15d-07b37e4eab8d · outbound

This paper cites In: Proceedings ECCV (2020).

PaCoNet: Deep Data Extraction for Parallel Coordinates In: Proceedings ECCV (2020)

Reference 14

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Observation 98882ac6-bed6-43d0-8f3b-8272208a7bb9 · outbound

This paper cites In: 2009 13th International Conference Information Visualisation (2009).

PaCoNet: Deep Data Extraction for Parallel Coordinates In: 2009 13th International Conference Information Visualisation (2009)

Reference 15

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Observation 092450a5-9961-4f7d-86e9-dc1ee8d33561 · outbound

This paper cites Data Extraction from Charts via Single Deep Neural Network.

PaCoNet: Deep Data Extraction for Parallel Coordinates Data Extraction from Charts via Single Deep Neural Network

Reference 16

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Observation f5ed702f-a5c8-4cdd-be26-7ce60ba4b699 · outbound

This paper cites BMC genomics6(1) (2005).

PaCoNet: Deep Data Extraction for Parallel Coordinates BMC genomics6(1) (2005)

Reference 17

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Observation 17dbdd2e-c31c-4d73-ba72-7e6e6378d554 · outbound

This paper cites In: Proceedings of WACV (2021).

PaCoNet: Deep Data Extraction for Parallel Coordinates In: Proceedings of WACV (2021)

Reference 18

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This paper cites In: Findings of the association for computational linguistics: ACL 2022 (2022).

PaCoNet: Deep Data Extraction for Parallel Coordinates In: Findings of the association for computational linguistics: ACL 2022 (2022)

Reference 19

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This paper cites In: Computer Graph- ics Forum (2008).

PaCoNet: Deep Data Extraction for Parallel Coordinates In: Computer Graph- ics Forum (2008)

Reference 20

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PaCoNet: Deep Data Extraction for Parallel Coordinates Unresolved cited work

Reference 21

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This paper cites In: 2023 International Conference on Digital Image Computing: Techniques and Applications (DICTA) (2023).

PaCoNet: Deep Data Extraction for Parallel Coordinates In: 2023 International Conference on Digital Image Computing: Techniques and Applications (DICTA) (2023)

Reference 22

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PaCoNet: Deep Data Extraction for Parallel Coordinates Unresolved cited work

Reference 23

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This paper cites In: Proceedings of WACV (2023).

PaCoNet: Deep Data Extraction for Parallel Coordinates In: Proceedings of WACV (2023)

Reference 24

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This paper cites In: Proceedings of CVPR (June 2019).

PaCoNet: Deep Data Extraction for Parallel Coordinates In: Proceedings of CVPR (June 2019)

Reference 25

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PaCoNet: Deep Data Extraction for Parallel Coordinates ArXiv (2015), https://api.semanticscholar.org/CorpusID: 3719281

Reference 26

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This paper cites IEEE TVCG (2016).

PaCoNet: Deep Data Extraction for Parallel Coordinates IEEE TVCG (2016)

Reference 27

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This paper cites In: Proceedings of the ACM Symposium on User Interface Software and Technology (UIST) (2011).

PaCoNet: Deep Data Extraction for Parallel Coordinates In: Proceedings of the ACM Symposium on User Interface Software and Technology (UIST) (2011)

Reference 28

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This paper cites Gemini: A Family of Highly Capable Multimodal Models.

PaCoNet: Deep Data Extraction for Parallel Coordinates Gemini: A Family of Highly Capable Multimodal Models

Reference 29

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This paper cites IEEE TVCG (2023).

PaCoNet: Deep Data Extraction for Parallel Coordinates IEEE TVCG (2023)

Reference 30

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PaCoNet: Deep Data Extraction for Parallel Coordinates Chapman and Hall/CRC (2018)

Reference 31

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PaCoNet: Deep Data Extraction for Parallel Coordinates Climate research (2005)

Reference 32

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This paper cites In: Proceedings of CVPR (2021).

PaCoNet: Deep Data Extraction for Parallel Coordinates In: Proceedings of CVPR (2021)

Reference 33

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This paper cites In: Proceedings of CVPR (2020).

PaCoNet: Deep Data Extraction for Parallel Coordinates In: Proceedings of CVPR (2020)

Reference 34

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This paper cites IEEE Transactions on Visualization and Computer Graphics (2009).

PaCoNet: Deep Data Extraction for Parallel Coordinates IEEE Transactions on Visualization and Computer Graphics (2009)

Reference 35

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raw_fallback, observed 2026-08-07T19:07:15.449294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T19:07:15.227993Z digest=sha256:b82ebd5bc3d7bf406889605c37eb7551e201c48cbf20fea5d5b030ff8f384178

Observation a39f7442-d7c6-42b7-8fb8-32e7c92d2eeb · outbound

This paper cites Journal of Visualization (2021).

PaCoNet: Deep Data Extraction for Parallel Coordinates Journal of Visualization (2021)

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T19:07:15.423874Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T19:07:15.233313Z digest=sha256:a6ff0644b59c1cd0444349173a08e1322c2cf53e65ed020e347edaae20de9525

Observation 2dd8bfa0-4d6b-442a-8f1d-083114a845e5 · outbound

This paper cites In: Computer Graphics Forum (Proc.

PaCoNet: Deep Data Extraction for Parallel Coordinates In: Computer Graphics Forum (Proc

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T19:07:15.401767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T19:07:15.240317Z digest=sha256:c45c1083515687deccf515844c964d0f3aec110790aa452c26dc9ffd78a89f6a

Pith citing papers

No inbound Pith citation observations are available.