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Paper Citation Record · LEDGER

Exploring Light-Weight Object Recognition for Real-Time Document Detection

As of 9 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:2509.06246.

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

pith.paper-citation-record.v1
2509.06246 v1

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T23:55:07.215424Z

measured 22 of 22 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

22 of 22 outbound references displayed

  • verified exact0
  • verified fuzzy16
  • unresolved6
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bc46f13d-d7fd-4439-b98f-0e3a34abc7d3 · outbound

This paper cites Few shots are all you need: A progressive learning approach for low resource handwritten text recognition,.

Exploring Light-Weight Object Recognition for Real-Time Document Detection Few shots are all you need: A progressive learning approach for low resource handwritten text recognition,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:55:07.566016Z

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.

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Observation 1f5daf95-7141-4064-8db9-198609f4d00f · outbound

This paper cites Efficient skew detection and correction in scanned document images through clustering of probabilistic hough transforms,.

Exploring Light-Weight Object Recognition for Real-Time Document Detection Efficient skew detection and correction in scanned document images through clustering of probabilistic hough transforms,

Reference 2

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verified fuzzy
raw_fallback, observed 2026-08-04T23:55:07.551631Z

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.

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Observation 310e76b4-8e74-42a4-a6e7-f089786047e0 · outbound

This paper cites Easyocr,.

Exploring Light-Weight Object Recognition for Real-Time Document Detection Easyocr,

Reference 3

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verified fuzzy
raw_fallback, observed 2026-08-04T23:55:07.537285Z

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.

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Observation 6a9069c2-f03b-4584-84ae-7840cbda2d60 · outbound

This paper cites Nbid dataset: Towards robust information extraction in official documents,.

Exploring Light-Weight Object Recognition for Real-Time Document Detection Nbid dataset: Towards robust information extraction in official documents,

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-04T23:55:07.523871Z

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.

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Observation ebd2dbe9-ccc2-4bea-a715-ffc2e9b89e56 · outbound

This paper cites A flexible approach for automatic license plate recognition in unconstrained scenarios,.

Exploring Light-Weight Object Recognition for Real-Time Document Detection A flexible approach for automatic license plate recognition in unconstrained scenarios,

Reference 5

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verified fuzzy
raw_fallback, observed 2026-08-04T23:55:07.509746Z

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.

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Observation 549aebb0-b023-4098-ab1e-22ac4285e692 · outbound

This paper cites Midv-2020: a comprehensive benchmark dataset for identity document analysis,.

Exploring Light-Weight Object Recognition for Real-Time Document Detection Midv-2020: a comprehensive benchmark dataset for identity document analysis,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:55:07.493414Z

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.

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Observation 74d49517-8ef6-4a56-b122-26683e5fe47e · outbound

This paper cites Gpt-4 technical report,.

Exploring Light-Weight Object Recognition for Real-Time Document Detection Gpt-4 technical report,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:55:07.477018Z

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.

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Observation e1f71bd5-21b0-4a71-8107-3b9c736522e5 · outbound

This paper cites Gemini: A family of highly capable multimodal models,.

Exploring Light-Weight Object Recognition for Real-Time Document Detection Gemini: A family of highly capable multimodal models,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:55:07.463445Z

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=2026-08-04T23:55:07.155581Z digest=sha256:df779452e102fe09a53189643f415af59ad6af9899e0fa5950215b0d2b925063

Observation efb929ae-cc6c-4df6-9871-ab6c89a05b27 · outbound

This paper cites Benchmarking vision-language models on optical character recognition in dynamic video environments,.

Exploring Light-Weight Object Recognition for Real-Time Document Detection Benchmarking vision-language models on optical character recognition in dynamic video environments,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:55:07.448155Z

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.

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Observation 7fdf8dd7-3e1b-4abe-8d12-d73a5afec025 · outbound

This paper cites Exploring OCR Capabilities of GPT-4V(ision) : A Quantitative and In-depth Evaluation.

Exploring Light-Weight Object Recognition for Real-Time Document Detection Exploring OCR Capabilities of GPT-4V(ision) : A Quantitative and In-depth Evaluation

Reference 10

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unresolved
no resolver link, observed 2026-08-04T23:55:07.168842Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation ee1a35f2-6ffc-43a7-b202-f7d50dc01f10 · outbound

This paper cites doctr: Document text recognition,.

Exploring Light-Weight Object Recognition for Real-Time Document Detection doctr: Document text recognition,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:55:07.430817Z

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.

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Observation 28c7831b-273a-432f-96dd-7ddde0a159f4 · outbound

This paper cites Character region awareness for text detection,.

Exploring Light-Weight Object Recognition for Real-Time Document Detection Character region awareness for text detection,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:55:07.416411Z

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=2026-08-04T23:55:07.177381Z digest=sha256:cd88c402fefa63dd475e738bd455e926340ec0808bb0e0d765cb60bcbeac1bcd

Observation c59ef504-0b04-4991-9e21-be62ee993636 · outbound

This paper cites Deep residual learning for image recognition,.

Exploring Light-Weight Object Recognition for Real-Time Document Detection Deep residual learning for image recognition,

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-04T23:55:07.181274Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation eb6f778e-d101-424d-a8b9-ce3896f3ea85 · outbound

This paper cites An end-to-end trainable neural network for image-based sequence recognition and its application to scene text recognition,.

Exploring Light-Weight Object Recognition for Real-Time Document Detection An end-to-end trainable neural network for image-based sequence recognition and its application to scene text recognition,

Reference 14

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unresolved
no resolver link, observed 2026-08-04T23:55:07.185408Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 10f71e43-103c-4f19-8d7d-37b7eb53062c · outbound

This paper cites You only look once: Unified, real-time object detection,.

Exploring Light-Weight Object Recognition for Real-Time Document Detection You only look once: Unified, real-time object detection,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:55:07.383261Z

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=2026-08-04T23:55:07.189602Z digest=sha256:d2ec9e2cecd65f6cc59d7f16e64fbf2116a98de9d29c2b21015a52529ed33790

Observation b95906c6-b73a-4f7b-985e-05c45ddeb301 · outbound

This paper cites RTMDet: An Empirical Study of Designing Real-Time Object Detectors.

Exploring Light-Weight Object Recognition for Real-Time Document Detection RTMDet: An Empirical Study of Designing Real-Time Object Detectors

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-04T23:55:07.193727Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T23:55:07.193727Z digest=sha256:086bbfa95d17d202f74e7fce43cd67ddba03bef40726efb404d0705a741ed664

Observation 44f2f24a-3018-4131-8f5c-817e14ab576f · outbound

This paper cites Focal loss for dense object detection,.

Exploring Light-Weight Object Recognition for Real-Time Document Detection Focal loss for dense object detection,

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-04T23:55:07.198014Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation d2ca97b1-ad01-4424-892b-9df195ba5fe6 · outbound

This paper cites Feature pyramid networks for object detection,.

Exploring Light-Weight Object Recognition for Real-Time Document Detection Feature pyramid networks for object detection,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:55:07.359907Z

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.

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Observation 1a492c79-878d-4555-89f1-be85d6a07294 · outbound

This paper cites Adaptive radial projection on fourier magnitude spectrum for document image skew estimation,.

Exploring Light-Weight Object Recognition for Real-Time Document Detection Adaptive radial projection on fourier magnitude spectrum for document image skew estimation,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:55:07.344980Z

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.

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Observation 5417c1b6-d533-44e2-ad6f-7b86b77ddf6b · outbound

This paper cites License plate detection and recognition in unconstrained scenarios,.

Exploring Light-Weight Object Recognition for Real-Time Document Detection License plate detection and recognition in unconstrained scenarios,

Reference 20

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verified fuzzy
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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.

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Observation d0b544e3-163f-443c-a030-93aa530f8cb6 · outbound

This paper cites Yolov11: An overview of the key architectural enhancements,.

Exploring Light-Weight Object Recognition for Real-Time Document Detection Yolov11: An overview of the key architectural enhancements,

Reference 21

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verified fuzzy
raw_fallback, observed 2026-08-04T23:55:07.313864Z

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.

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Observation c41841b0-92d2-4399-82da-01cafed1542a · outbound

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

Exploring Light-Weight Object Recognition for Real-Time Document Detection Gemini: A Family of Highly Capable Multimodal Models

Reference 2024

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unresolved
no resolver link, observed 2026-08-04T23:55:07.159836Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Pith citing papers

No inbound Pith citation observations are available.