Paper Citation Record · LEDGER

Divide and Conquer: Grounding a Bleeding Areas in Gastrointestinal Image with Two-Stage Model

As of 21 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 1 inbound Pith citation observation for arXiv:2412.16723.

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

pith.paper-citation-record.v1
2412.16723 v1

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T10:21:59.244394Z

measured 23 of 23 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-22T07:32:05.152342Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T07:34:42.694013Z

Reference resolution

22 of 22 outbound references displayed

verified exact1
verified fuzzy15
unresolved6
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 538a0e37-8be4-4395-b08d-e8534bbd4799 · outbound

This paper cites Auto- wcebleedgen version v1 and v2: Challenge, datasets and evaluation.

Divide and Conquer: Grounding a Bleeding Areas in Gastrointestinal Image with Two-Stage Model Auto- wcebleedgen version v1 and v2: Challenge, datasets and evaluation

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:21:59.467294Z

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 092bea80-54ef-4590-930d-4cfee9e0bd21 · outbound

This paper cites Wcebleedgen: A wireless capsule en- doscopy dataset containing bleeding and non-bleeding frames.https://zenodo.

Divide and Conquer: Grounding a Bleeding Areas in Gastrointestinal Image with Two-Stage Model Wcebleedgen: A wireless capsule en- doscopy dataset containing bleeding and non-bleeding frames.https://zenodo

Reference 2

Resolution: verified exact; raw_fallback, observed 2026-08-11T10:21:59.327234Z

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 5fe10b35-bf49-4bdc-acb4-ca776b792854 · outbound

This paper cites Autowcebleedgen-test dataset (improved).

Divide and Conquer: Grounding a Bleeding Areas in Gastrointestinal Image with Two-Stage Model Autowcebleedgen-test dataset (improved)

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:21:59.459634Z

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 025d875d-411b-4b7a-9d3c-1bd8026be339 · outbound

This paper cites Bagoftricksofhybridnetworkforcovid-19detectionofctscans.

Divide and Conquer: Grounding a Bleeding Areas in Gastrointestinal Image with Two-Stage Model Bagoftricksofhybridnetworkforcovid-19detectionofctscans

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:21:59.452091Z

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 d3ae91f4-7d5b-4f92-9053-65813c122e96 · outbound

This paper cites A closer look at spatial-slice features learning for covid-19 detection.

Divide and Conquer: Grounding a Bleeding Areas in Gastrointestinal Image with Two-Stage Model A closer look at spatial-slice features learning for covid-19 detection

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:21:59.444760Z

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 59039cbd-b93c-48e9-9d2f-e7b63557c03d · outbound

This paper cites Strong baseline and bag of tricks for covid-19 detection of ct scans, 2023.

Divide and Conquer: Grounding a Bleeding Areas in Gastrointestinal Image with Two-Stage Model Strong baseline and bag of tricks for covid-19 detection of ct scans, 2023

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:21:59.436911Z

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 13353ada-2b1e-48eb-b72a-733ce85e6088 · outbound

This paper cites Simple 2d convolutional neural network- based approach for covid-19 detection, 2024.

Divide and Conquer: Grounding a Bleeding Areas in Gastrointestinal Image with Two-Stage Model Simple 2d convolutional neural network- based approach for covid-19 detection, 2024

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:21:59.428820Z

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 10b49bdf-dfce-4c40-972c-1bc443f95ca0 · outbound

This paper cites Deep multi-modal object detection and semantic segmentation for autonomous driving: Datasets, methods, and challenges.

Divide and Conquer: Grounding a Bleeding Areas in Gastrointestinal Image with Two-Stage Model Deep multi-modal object detection and semantic segmentation for autonomous driving: Datasets, methods, and challenges

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:21:59.421111Z

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 d84650da-715d-49a7-804c-9579c619329b · outbound

This paper cites Adversarial multi-task label embedding for text classification.

Divide and Conquer: Grounding a Bleeding Areas in Gastrointestinal Image with Two-Stage Model Adversarial multi-task label embedding for text classification

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:21:59.413324Z

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 fb228227-5d4a-4de8-9b48-fdc1849f1d03 · outbound

This paper cites A multi-task learning framework for automated segmentation and classi- fication of breast tumors from ultrasound images.Ultrasonic imaging, 44(1):3–12, 2022.

Divide and Conquer: Grounding a Bleeding Areas in Gastrointestinal Image with Two-Stage Model A multi-task learning framework for automated segmentation and classi- fication of breast tumors from ultrasound images.Ultrasonic imaging, 44(1):3–12, 2022

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:21:59.405722Z

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 6048b92e-b62e-4eab-bc6d-ff438edcb609 · outbound

This paper cites Multi-Task Learning with Deep Neural Networks: A Survey.

Divide and Conquer: Grounding a Bleeding Areas in Gastrointestinal Image with Two-Stage Model Multi-Task Learning with Deep Neural Networks: A Survey

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-11T10:21:59.208012Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 147e4697-aea0-47c4-bfc7-0877534d6fcd · outbound

This paper cites Averaging Weights Leads to Wider Optima and Better Generalization.

Divide and Conquer: Grounding a Bleeding Areas in Gastrointestinal Image with Two-Stage Model Averaging Weights Leads to Wider Optima and Better Generalization

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-11T10:21:59.211114Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b32447f9-525b-4cba-8d6a-914e31ad2162 · outbound

This paper cites Memo: Test time robustness via adaptation and augmentation.

Divide and Conquer: Grounding a Bleeding Areas in Gastrointestinal Image with Two-Stage Model Memo: Test time robustness via adaptation and augmentation

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:21:59.397719Z

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 320c5ad0-9153-45db-8199-56b9ddbc462e · outbound

This paper cites Efficientnet: Rethinking model scaling for convolu- tional neural networks.

Divide and Conquer: Grounding a Bleeding Areas in Gastrointestinal Image with Two-Stage Model Efficientnet: Rethinking model scaling for convolu- tional neural networks

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-11T10:21:59.216808Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc9dc0f3-dc6c-4ec6-8fbe-d40a948c536e · outbound

This paper cites Pytorch image models.

Divide and Conquer: Grounding a Bleeding Areas in Gastrointestinal Image with Two-Stage Model Pytorch image models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-11T10:21:59.219795Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ee1d2b5c-c19c-4df8-9175-f6ccbfb3314a · outbound

This paper cites A convnet for the 2020s.

Divide and Conquer: Grounding a Bleeding Areas in Gastrointestinal Image with Two-Stage Model A convnet for the 2020s

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:21:59.381337Z

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 4fb82f75-b207-47df-80f9-4be74e665c92 · outbound

This paper cites Internimage: Exploring large-scale vision foundation models with deformable con- volutions.

Divide and Conquer: Grounding a Bleeding Areas in Gastrointestinal Image with Two-Stage Model Internimage: Exploring large-scale vision foundation models with deformable con- volutions

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:21:59.372857Z

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 8c3df6fb-aba2-48c2-a960-95b5ea82e0f1 · outbound

This paper cites Mmdetection: Open mmlab detection toolbox and benchmark, 2019.

Divide and Conquer: Grounding a Bleeding Areas in Gastrointestinal Image with Two-Stage Model Mmdetection: Open mmlab detection toolbox and benchmark, 2019

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:21:59.364232Z

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 79a833f5-1cf4-4446-bf48-f39ebba830a7 · outbound

This paper cites Decoupled weight decay regularization, 2019.

Divide and Conquer: Grounding a Bleeding Areas in Gastrointestinal Image with Two-Stage Model Decoupled weight decay regularization, 2019

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-11T10:21:59.234155Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4452c3da-5adc-4038-aba2-793859111a72 · outbound

This paper cites Mixed precision training, 2018.

Divide and Conquer: Grounding a Bleeding Areas in Gastrointestinal Image with Two-Stage Model Mixed precision training, 2018

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-11T10:21:59.238045Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4d2af15a-52fc-477b-8b97-098a08ce95cc · outbound

This paper cites Cubuk, Barret Zoph, Jonathon Shlens, and Quoc V.

Divide and Conquer: Grounding a Bleeding Areas in Gastrointestinal Image with Two-Stage Model Cubuk, Barret Zoph, Jonathon Shlens, and Quoc V

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:21:59.345363Z

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 435edc4b-a88e-4f56-9a10-19342889f1f3 · outbound

This paper cites Pytorch library for cam methods.

Divide and Conquer: Grounding a Bleeding Areas in Gastrointestinal Image with Two-Stage Model Pytorch library for cam methods

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:21:59.336482Z

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.

Pith citing papers

Observation 2210be72-fa00-46d7-a0bf-58dbc7d9fded · inbound

VISTA: Validation-Guided Integration of Spatial and Temporal Foundation Models with Anatomical Decoding for Rare-Pathology VCE Event Detection -- after competition results cites this paper.

VISTA: Validation-Guided Integration of Spatial and Temporal Foundation Models with Anatomical Decoding for Rare-Pathology VCE Event Detection -- after competition results Divide and Conquer: Grounding a Bleeding Areas in Gastrointestinal Image with Two-Stage Model

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-22T07:34:42.697021Z

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.