Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines | Paper Citation Record

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This paper cites In: Proceedings of the International Conference on Learning Representations (ICLR) (2020), https: //openreview.net/forum?id=ryghZJBKPS.

Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines In: Proceedings of the International Conference on Learning Representations (ICLR) (2020), https: //openreview.net/forum?id=ryghZJBKPS

Reference 1

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This paper cites In: European Conference on Computer Vision (2024), https://api.semanticscholar.org/CorpusID:271244923.

Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines In: European Conference on Computer Vision (2024), https://api.semanticscholar.org/CorpusID:271244923

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:31:41.520325Z

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This paper cites In: ICLR (2025).

Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines In: ICLR (2025)

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:31:41.478322Z

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This paper cites International Journal on Docu- ment Analysis and Recognition27, 317–334 (2024).

Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines International Journal on Docu- ment Analysis and Recognition27, 317–334 (2024)

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:31:41.480533Z

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This paper cites In: International Conference on Learning Representations (ICLR) (2024).

Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines In: International Conference on Learning Representations (ICLR) (2024)

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:31:41.472323Z

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This paper cites In: European Conference on Computer Vision (ECCV).

Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines In: European Conference on Computer Vision (ECCV)

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:31:41.462652Z

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This paper cites In: IEEE/CVF International Conference on Computer Vision (ICCV).

Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines In: IEEE/CVF International Conference on Computer Vision (ICCV)

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:31:41.486455Z

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This paper cites In: Proceedings of the 37th International Conference on Machine Learning (ICML).

Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines In: Proceedings of the 37th International Conference on Machine Learning (ICML)

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:31:41.514155Z

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This paper cites In: Proceedings of the 32nd International ACM SIGIR Conference on Research and Development in Information Retrieval.

Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines In: Proceedings of the 32nd International ACM SIGIR Conference on Research and Development in Information Retrieval

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:31:41.458554Z

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This paper cites In: international conference on machine learning.

Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines In: international conference on machine learning

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:31:41.448820Z

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This paper cites In: International conference on machine learning.

Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines In: International conference on machine learning

Reference 11

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This paper cites 2019 International Conference on Document Analysis and Recognition (ICDAR) pp.

Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines 2019 International Conference on Document Analysis and Recognition (ICDAR) pp

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:31:41.456569Z

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This paper cites In: Inter- national Conference on Document Analysis and Recognition.

Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines In: Inter- national Conference on Document Analysis and Recognition

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:31:41.474250Z

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This paper cites 2013 12th International Conference on Document Analysis and Recognition pp.

Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines 2013 12th International Conference on Document Analysis and Recognition pp

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:31:41.438093Z

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This paper cites In: Proceedings of the 34th International Conference on Machine Learning (ICML).

Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines In: Proceedings of the 34th International Conference on Machine Learning (ICML)

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:31:41.516031Z

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This paper cites In: International Conference on Machine Learning (ICML).

Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines In: International Conference on Machine Learning (ICML)

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:31:41.468470Z

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This paper cites In: Document Analysis and Recognition (ICDAR).

Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines In: Document Analysis and Recognition (ICDAR)

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:31:41.501942Z

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This paper cites ACM Computing Surveys56, 1 – 41 (2022), https://api.semanticscholar.org/CorpusID:253553399.

Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines ACM Computing Surveys56, 1 – 41 (2022), https://api.semanticscholar.org/CorpusID:253553399

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:31:41.493078Z

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This paper cites In: International Joint Conference on Artificial Intelligence (IJCAI) (2024).

Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines In: International Joint Conference on Artificial Intelligence (IJCAI) (2024)

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:31:41.524705Z

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This paper cites In: European Conference on Computer Vision (ECCV) (2022).

Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines In: European Conference on Computer Vision (ECCV) (2022)

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:31:41.439893Z

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This paper cites In: Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (1994), https://api.semanticscholar.org/CorpusID:915058.

Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines In: Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (1994), https://api.semanticscholar.org/CorpusID:915058

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:31:41.443895Z

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This paper cites In: Proceedings of the 30th ACM International Conference on Multimedia.

Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines In: Proceedings of the 30th ACM International Conference on Multimedia

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:31:41.497389Z

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This paper cites Pattern Recognition157, 110816 (2025).

Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines Pattern Recognition157, 110816 (2025)

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:31:41.450690Z

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This paper cites In: Advances in Neural Information Processing Systems (NeurIPS).

Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines In: Advances in Neural Information Processing Systems (NeurIPS)

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:31:41.445631Z

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This paper cites In: Proceedings of the IEEE/CVF International Conference on Computer Vision.

Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines In: Proceedings of the IEEE/CVF International Conference on Computer Vision

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:31:41.460497Z

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This paper cites In: IEEE/CVF International Conference on Computer Vision (ICCV) (2025).

Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines In: IEEE/CVF International Conference on Computer Vision (ICCV) (2025)

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:31:41.452743Z

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This paper cites In: International Conference on Learning Representations (ICLR) (2025).

Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines In: International Conference on Learning Representations (ICLR) (2025)

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:31:41.522367Z

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This paper cites ACM Computing Surveys (CSUR)54, 1 – 40 (2020), https://api.semanticscholar.org/CorpusID:221397441.

Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines ACM Computing Surveys (CSUR)54, 1 – 40 (2020), https://api.semanticscholar.org/CorpusID:221397441

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:31:41.499519Z

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Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines In: AAAI

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:31:41.503852Z

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Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines Unresolved cited work

Reference 30

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This paper cites Social Choice and Welfare 36(2), 267–303 (2011).

Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines Social Choice and Welfare 36(2), 267–303 (2011)

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:31:41.507949Z

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This paper cites In: International Conference on Learning Representations (ICLR) (2018).

Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines In: International Conference on Learning Representations (ICLR) (2018)

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:31:41.518235Z

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Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines org/CorpusID:324600

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:31:41.441786Z

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This paper cites In: Docu- ment Analysis and Recognition (ICDAR) (2024).

Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines In: Docu- ment Analysis and Recognition (ICDAR) (2024)

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:31:41.464569Z

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This paper cites In: Proceedings of the Fifth Workshop on Natural Language Processing and Computational Social Science (NLP+CSS).

Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines In: Proceedings of the Fifth Workshop on Natural Language Processing and Computational Social Science (NLP+CSS)

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:31:41.466701Z

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Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:31:41.512004Z

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This paper cites In: Document Analysis and Recognition (ICDAR).

Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines In: Document Analysis and Recognition (ICDAR)

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:31:41.509995Z

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Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines In: Document Analysis and Recognition – ICDAR 2023

Reference 38

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This paper cites In: Winter Conference on Applications of Computer Vision (WACV) (2025).

Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines In: Winter Conference on Applications of Computer Vision (WACV) (2025)

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:31:41.505976Z

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Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines In: International Conference on Document Analysis and Recognition (IC- DAR) (2025)

Reference 40

Resolution: verified exact; doi, observed 2026-07-02T14:27:02.936599Z

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Observation b93e299a-5fe1-4eba-bb14-dbb837abf8c1 · outbound

This paper cites In: European Conference on Computer Vision (ECCV) (2024).

Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines In: European Conference on Computer Vision (ECCV) (2024)

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:31:41.488833Z

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This paper cites Parcham, M.

Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines Parcham, M

Reference 42

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This paper cites Advances in Neural Information Processing Systems35, 22354–22367 (2022).

Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines Advances in Neural Information Processing Systems35, 22354–22367 (2022)

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:31:41.490894Z

Source-reported events for the cited work

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Observation 3973218d-5679-422f-8c98-d95b3c73be10 · outbound

This paper cites In: Findings of the Association for Computational Linguistics: EMNLP.

Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines In: Findings of the Association for Computational Linguistics: EMNLP

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:31:41.436158Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 08f9dda1-fa08-4eab-8984-f79865aa039c · outbound

This paper cites 2021 IEEE Winter Conference on Applications of Computer Vision (WACV) pp.

Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines 2021 IEEE Winter Conference on Applications of Computer Vision (WACV) pp

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:31:41.454602Z

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Observation 1375acae-f236-48a5-a8b1-f1e5dbb756e5 · outbound

This paper cites In: European Conference on Computer Vision (ECCV).

Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines In: European Conference on Computer Vision (ECCV)

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:31:41.482967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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