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Paper Citation Record · LEDGER

ProgRoCC: A Progressive Approach to Rough Crowd Counting

As of 22 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2504.13405.

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

pith.paper-citation-record.v1
2504.13405 v1

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:11:57.501216Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+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

33 of 33 outbound references displayed

  • verified exact0
  • verified fuzzy29
  • unresolved4
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation baa22664-f6f6-4001-8ee6-a54604a8e4fe · outbound

This paper cites Completely self-supervised crowd counting via dis- tribution matching.

ProgRoCC: A Progressive Approach to Rough Crowd Counting Completely self-supervised crowd counting via dis- tribution matching

Reference 1

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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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Observation 4444024c-6a93-4e6f-b1d8-3a2b2ebf22ff · outbound

This paper cites Multi-task semi-supervised crowd counting via global to local self-correction.

ProgRoCC: A Progressive Approach to Rough Crowd Counting Multi-task semi-supervised crowd counting via global to local self-correction

Reference 2

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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 2026-08-21T06:32:19.484+00:00.

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Observation 3baffeff-ace5-4b30-80e0-e064e26754fa · outbound

This paper cites A primarily se- rial, foveal accumulator underlies approximate numerical es- timation.

ProgRoCC: A Progressive Approach to Rough Crowd Counting A primarily se- rial, foveal accumulator underlies approximate numerical es- timation

Reference 3

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Source-reported events for the cited work

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Observation 73855180-5835-4f6d-a6eb-dc7c007856a7 · outbound

This paper cites Redesigning multi-scale neural network for crowd counting.

ProgRoCC: A Progressive Approach to Rough Crowd Counting Redesigning multi-scale neural network for crowd counting

Reference 4

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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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Observation b095c814-240c-4201-8af6-63060a65d382 · outbound

This paper cites Densitytoken: Weakly-supervised crowd counting with density classifica- tion.

ProgRoCC: A Progressive Approach to Rough Crowd Counting Densitytoken: Weakly-supervised crowd counting with density classifica- tion

Reference 5

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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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Observation f3ce6e6f-746f-4eda-a963-237cb37fc5d6 · outbound

This paper cites Counting crowds in bad weather.

ProgRoCC: A Progressive Approach to Rough Crowd Counting Counting crowds in bad weather

Reference 6

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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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Observation 4fc86dc8-b9d6-4242-aa74-75f2c1aa6d11 · outbound

This paper cites Composition loss for counting, density map estima- tion and localization in dense crowds.

ProgRoCC: A Progressive Approach to Rough Crowd Counting Composition loss for counting, density map estima- tion and localization in dense crowds

Reference 7

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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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Observation 29dea14a-1690-4955-b9f0-147e24b82b0b · outbound

This paper cites Clip- count: Towards text-guided zero-shot object counting.

ProgRoCC: A Progressive Approach to Rough Crowd Counting Clip- count: Towards text-guided zero-shot object counting

Reference 8

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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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Observation fdc10049-eb2e-4ebe-b5bc-b4e292011206 · outbound

This paper cites Knowledge-aware prompt tun- ing for generalizable vision-language models.

ProgRoCC: A Progressive Approach to Rough Crowd Counting Knowledge-aware prompt tun- ing for generalizable vision-language models

Reference 9

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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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Observation 3d370084-563a-45be-a851-fd763fdd4490 · outbound

This paper cites To- wards using count-level weak supervision for crowd count- ing.

ProgRoCC: A Progressive Approach to Rough Crowd Counting To- wards using count-level weak supervision for crowd count- ing

Reference 10

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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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Observation 8e905cb5-258c-49c8-af34-b9b8da9d0a13 · outbound

This paper cites Csrnet: Di- lated convolutional neural networks for understanding the highly congested scenes.

ProgRoCC: A Progressive Approach to Rough Crowd Counting Csrnet: Di- lated convolutional neural networks for understanding the highly congested scenes

Reference 11

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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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Observation 573b1948-390e-49a2-879f-eb0f855f4b63 · outbound

This paper cites Transcrowd: Weakly-supervised crowd counting with transformers.

ProgRoCC: A Progressive Approach to Rough Crowd Counting Transcrowd: Weakly-supervised crowd counting with transformers

Reference 12

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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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Observation 842d489d-2987-45a4-a160-cf30a4535c58 · outbound

This paper cites An end-to-end transformer model for crowd localization.

ProgRoCC: A Progressive Approach to Rough Crowd Counting An end-to-end transformer model for crowd localization

Reference 13

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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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Observation 40951669-ceaf-4f71-9f8b-47d639324027 · outbound

This paper cites Crowdclip: Unsupervised crowd counting via vision-language model.

ProgRoCC: A Progressive Approach to Rough Crowd Counting Crowdclip: Unsupervised crowd counting via vision-language model

Reference 14

Resolution
verified fuzzy
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Source-reported events for the cited work

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

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Observation 96d09bd4-bda0-4c5b-8417-7b941911e853 · outbound

This paper cites Point-query quadtree for crowd counting, localization, and more.

ProgRoCC: A Progressive Approach to Rough Crowd Counting Point-query quadtree for crowd counting, localization, and more

Reference 15

Resolution
verified fuzzy
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Source-reported events for the cited work

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

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Observation 9dbe3d84-c802-4407-af9c-8ebecc9131c8 · outbound

This paper cites Semi-supervised crowd counting via self-training on surrogate tasks.

ProgRoCC: A Progressive Approach to Rough Crowd Counting Semi-supervised crowd counting via self-training on surrogate tasks

Reference 16

Resolution
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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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Observation 5720ed65-0ef5-49e5-a996-d75e55635dd9 · outbound

This paper cites Bayesian loss for crowd count estimation with point super- vision.

ProgRoCC: A Progressive Approach to Rough Crowd Counting Bayesian loss for crowd count estimation with point super- vision

Reference 17

Resolution
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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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Observation 1e0348f1-ba96-43a6-a0eb-3727e069f99d · outbound

This paper cites S-clip: Semi-supervised vision-language learning us- ing few specialist captions.

ProgRoCC: A Progressive Approach to Rough Crowd Counting S-clip: Semi-supervised vision-language learning us- ing few specialist captions

Reference 18

Resolution
verified fuzzy
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Source-reported events for the cited work

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

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Observation e8a66e3f-a05c-4006-a57f-4aa9ee883045 · outbound

This paper cites Crowd counting with decomposed uncertainty.

ProgRoCC: A Progressive Approach to Rough Crowd Counting Crowd counting with decomposed uncertainty

Reference 19

Resolution
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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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Observation e050b1a5-d959-4b36-9792-0752af487ea0 · outbound

This paper cites Teaching clip to count to ten.

ProgRoCC: A Progressive Approach to Rough Crowd Counting Teaching clip to count to ten

Reference 20

Resolution
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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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Observation bdcce181-d7bb-4871-9d82-5ba9f9813b1d · outbound

This paper cites Semi-supervised crowd counting with contextual modeling: facilitating holistic un- derstanding of crowd scenes.

ProgRoCC: A Progressive Approach to Rough Crowd Counting Semi-supervised crowd counting with contextual modeling: facilitating holistic un- derstanding of crowd scenes

Reference 21

Resolution
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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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Observation 4d05a29c-610a-440b-8b75-8f929c82d089 · outbound

This paper cites Learn- ing transferable visual models from natural language super- vision.

ProgRoCC: A Progressive Approach to Rough Crowd Counting Learn- ing transferable visual models from natural language super- vision

Reference 22

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Observation 5b54c282-e5d6-41c8-a728-7debe623517a · outbound

This paper cites Crowd- diff: Multi-hypothesis crowd density estimation using dif- fusion models.

ProgRoCC: A Progressive Approach to Rough Crowd Counting Crowd- diff: Multi-hypothesis crowd density estimation using dif- fusion models

Reference 23

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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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Observation fcd1c559-a455-4629-8f91-84d19c1535e8 · outbound

This paper cites Almost unsupervised learning for dense crowd counting.

ProgRoCC: A Progressive Approach to Rough Crowd Counting Almost unsupervised learning for dense crowd counting

Reference 24

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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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Observation 4cf747ba-d727-4a19-a458-d528e7b3b678 · outbound

This paper cites Locate, size, and count: accurately re- solving people in dense crowds via detection.

ProgRoCC: A Progressive Approach to Rough Crowd Counting Locate, size, and count: accurately re- solving people in dense crowds via detection

Reference 25

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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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Observation fc47e3be-5d74-4f67-800c-b09826ac0b7f · outbound

This paper cites Jhu-crowd++: Large-scale crowd counting dataset and a benchmark method.

ProgRoCC: A Progressive Approach to Rough Crowd Counting Jhu-crowd++: Large-scale crowd counting dataset and a benchmark method

Reference 26

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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 2026-08-21T06:32:19.484+00:00.

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Observation 285a8374-14a3-4f1d-8804-f9a64e477b77 · outbound

This paper cites CCTrans: Simplifying and Improving Crowd Counting with Transformer.

ProgRoCC: A Progressive Approach to Rough Crowd Counting CCTrans: Simplifying and Improving Crowd Counting with Transformer

Reference 27

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation b8980985-e729-43f7-ba35-271b4367e31e · outbound

This paper cites Robust Zero-Shot Crowd Counting and Localization With Adaptive Resolution SAM.

ProgRoCC: A Progressive Approach to Rough Crowd Counting Robust Zero-Shot Crowd Counting and Localization With Adaptive Resolution SAM

Reference 28

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 3646dbdb-6b1a-4ba3-b2be-01c90ed210a7 · outbound

This paper cites Distribution matching for crowd counting.

ProgRoCC: A Progressive Approach to Rough Crowd Counting Distribution matching for crowd counting

Reference 29

Resolution
verified fuzzy
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Source-reported events for the cited work

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

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Observation d5a33e38-22e9-441c-acba-8fab5c10bebf · outbound

This paper cites Self-supervised learning with data-efficient su- pervised fine-tuning for crowd counting.

ProgRoCC: A Progressive Approach to Rough Crowd Counting Self-supervised learning with data-efficient su- pervised fine-tuning for crowd counting

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T12:11:57.612159Z

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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Observation 93636f85-e0d3-47c4-a942-29a4a83f5388 · outbound

This paper cites Single-image crowd counting via multi-column convolutional neural network.

ProgRoCC: A Progressive Approach to Rough Crowd Counting Single-image crowd counting via multi-column convolutional neural network

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T12:11:57.595623Z

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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Observation ffd1d692-2a55-4a44-9905-1aed336d3352 · outbound

This paper cites Contrastive learning of medical visual representations from paired images and text.

ProgRoCC: A Progressive Approach to Rough Crowd Counting Contrastive learning of medical visual representations from paired images and text

Reference 32

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation a99b8b5d-8b9e-4385-83a9-3270a6fb2902 · outbound

This paper cites Locality-aware crowd counting.

ProgRoCC: A Progressive Approach to Rough Crowd Counting Locality-aware crowd counting

Reference 33

Resolution
verified fuzzy
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Source-reported events for the cited work

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

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Pith citing papers

No inbound Pith citation observations are available.