Pith. sign in

Paper Citation Record · LEDGER

Data Augmentation with Diffusion Models for Colon Polyp Localization on the Low Data Regime: How much real data is enough?

As of 19 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 0 inbound Pith citation observations for arXiv:2411.18926.

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

pith.paper-citation-record.v1
2411.18926 v1

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T10:49:00.589469Z

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

27 of 27 outbound references displayed

  • verified exact1
  • verified fuzzy18
  • unresolved8
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5e57c7c3-a26f-49b3-a9ef-a4b7cca6d282 · outbound

This paper cites A multi-centre polyp detection and segmentation dataset for generalisability assessment.

Data Augmentation with Diffusion Models for Colon Polyp Localization on the Low Data Regime: How much real data is enough? A multi-centre polyp detection and segmentation dataset for generalisability assessment

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:49:00.831358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T10:49:00.502548Z digest=sha256:41e4ed22c558ce65242e09cead63331959ecb8234bed26149e31962b4061ff3a

Observation f1cd4b9a-a829-4f53-a205-f9e286e5f135 · outbound

This paper cites Randaugment: Practical au- tomated data augmentation with a reduced search space.

Data Augmentation with Diffusion Models for Colon Polyp Localization on the Low Data Regime: How much real data is enough? Randaugment: Practical au- tomated data augmentation with a reduced search space

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:49:00.822777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T10:49:00.506763Z digest=sha256:1cff9d325c9d33fe11ae8a8f7531ef3230a1493551a5cc226bd5cec18ac65f45

Observation 7add4d83-ed78-4785-88e4-60550dbf100d · outbound

This paper cites Arsdm: colonoscopy images synthesis with adaptive refinement semantic diffusion models.

Data Augmentation with Diffusion Models for Colon Polyp Localization on the Low Data Regime: How much real data is enough? Arsdm: colonoscopy images synthesis with adaptive refinement semantic diffusion models

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:49:00.814025Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T10:49:00.510356Z digest=sha256:c959ab5e2e8f1e4ab170b235dc19f2168d437c3e4bcf02e50367d18fed5fc4c1

Observation 6449c7ad-bc49-4a76-982c-fcd3623f6653 · outbound

This paper cites Colonformer: An efficient transformer based method for colon polyp segmentation.

Data Augmentation with Diffusion Models for Colon Polyp Localization on the Low Data Regime: How much real data is enough? Colonformer: An efficient transformer based method for colon polyp segmentation

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:49:00.805458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T10:49:00.514078Z digest=sha256:30573901b15ea52e4edb1a53fce00eda8d3c13820aeac9364e06dab802aabb88

Observation 5fede2ef-9f73-4a37-886c-35ec12139f3b · outbound

This paper cites The Pile: An 800GB Dataset of Diverse Text for Language Modeling.

Data Augmentation with Diffusion Models for Colon Polyp Localization on the Low Data Regime: How much real data is enough? The Pile: An 800GB Dataset of Diverse Text for Language Modeling

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-12T10:49:00.517978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:49:00.517978Z digest=sha256:c8b71bf7748f040bc74d8376e4d5f5edb61671305ed5ae8ce37eb5c0ac8837dd

Observation 6b42cfc1-8891-4a8e-b26d-d56663279635 · outbound

This paper cites Is synthetic data from generative models ready for image recognition?.

Data Augmentation with Diffusion Models for Colon Polyp Localization on the Low Data Regime: How much real data is enough? Is synthetic data from generative models ready for image recognition?

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-12T10:49:00.522078Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:49:00.522078Z digest=sha256:ab70e186c9d16b47c98f88d6f48f3d13e3484b8be31fd5ec9ff52a09036ddca4

Observation a0ff5b60-1735-4c89-8b6e-ea1e8976ab81 · outbound

This paper cites Denoising diffusion probabilistic models.

Data Augmentation with Diffusion Models for Colon Polyp Localization on the Low Data Regime: How much real data is enough? Denoising diffusion probabilistic models

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-12T10:49:00.525973Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:49:00.525973Z digest=sha256:35724b42297ba6544db12bb37555753afeda4b5f6cbcfba8e28af679cbd4b95a

Observation 7af2883a-f95a-4cb1-888a-73568d178121 · outbound

This paper cites Computer-aided diagnosis for optical diagnosis of diminutive colorectal polyps including sessile serrated lesions: a real-time comparison with screening endoscopists.

Data Augmentation with Diffusion Models for Colon Polyp Localization on the Low Data Regime: How much real data is enough? Computer-aided diagnosis for optical diagnosis of diminutive colorectal polyps including sessile serrated lesions: a real-time comparison with screening endoscopists

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:49:00.791807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T10:49:00.529102Z digest=sha256:ada6d4f625a17bd4baace16c1f6328abca00041932151ace3f0ecb4b1622ab66

Observation a35edd0c-63e2-4559-8d5c-8307bf446dcc · outbound

This paper cites Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen.

Data Augmentation with Diffusion Models for Colon Polyp Localization on the Low Data Regime: How much real data is enough? Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-12T10:49:00.532586Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:49:00.532586Z digest=sha256:575199a72f3e670ff5e897a9c260cf8c630917b4472c1dce1eb57bdd5072f65b

Observation de840d77-c909-4df3-9408-4f976bd3ede4 · outbound

This paper cites Quilt-1M: One Million Image-Text Pairs for Histopathology.

Data Augmentation with Diffusion Models for Colon Polyp Localization on the Low Data Regime: How much real data is enough? Quilt-1M: One Million Image-Text Pairs for Histopathology

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-12T10:49:00.536086Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:49:00.536086Z digest=sha256:ee5b6c5350c72d9a72b863f25f4d22127748ed69227dd30cb2d2ccb823fb1bf4

Observation 4e4fbf81-45c4-46a6-93d4-bfab9bbaecad · outbound

This paper cites Kvasir-seg: A segmented polyp dataset.

Data Augmentation with Diffusion Models for Colon Polyp Localization on the Low Data Regime: How much real data is enough? Kvasir-seg: A segmented polyp dataset

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:49:00.777890Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T10:49:00.539706Z digest=sha256:9f376809209b2c47d4060fa96ddc0aecbeee49e319309d09e5b3059c648bdf78

Observation a7f9a36a-71bc-4d6b-92b4-59216976e16f · outbound

This paper cites Improved Precision and Recall Metric for Assessing Generative Models.

Data Augmentation with Diffusion Models for Colon Polyp Localization on the Low Data Regime: How much real data is enough? Improved Precision and Recall Metric for Assessing Generative Models

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-12T10:49:00.543169Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:49:00.543169Z digest=sha256:db1186c51be5123191811fddc46ccedea3498e57340faa6584ad93835bec0efa

Observation 63d57aa0-3dae-4554-9af7-0520a33117ee · outbound

This paper cites Colonoscopy polyp detection and classification: Dataset creation and comparative evaluations.

Data Augmentation with Diffusion Models for Colon Polyp Localization on the Low Data Regime: How much real data is enough? Colonoscopy polyp detection and classification: Dataset creation and comparative evaluations

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:49:00.767424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T10:49:00.546895Z digest=sha256:3f1bae90609e53b902329c7e0f3fe4083698cbf7dabf56f79d37f51b97b19421

Observation fe7f6a83-4d69-4469-a4a4-d40f031bdf74 · outbound

This paper cites Repaint: Inpainting using denoising diffusion probabilistic models.

Data Augmentation with Diffusion Models for Colon Polyp Localization on the Low Data Regime: How much real data is enough? Repaint: Inpainting using denoising diffusion probabilistic models

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:49:00.758067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T10:49:00.550024Z digest=sha256:e8f459a56c6d4eba0b65404b3e776dd6a8e9e292a9ea3dcb85b32c33b1e69567

Observation f127f1c2-e059-4f5b-8fe6-ef85b61c2ac4 · outbound

This paper cites LDPolypVideo benchmark: a large-scale colonoscopy video dataset of diverse polyps.

Data Augmentation with Diffusion Models for Colon Polyp Localization on the Low Data Regime: How much real data is enough? LDPolypVideo benchmark: a large-scale colonoscopy video dataset of diverse polyps

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:49:00.749168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T10:49:00.553180Z digest=sha256:ae6a8f42e8bb31618cf7293f038cc1fb9ba92228092ad72276892bc7acf02a61

Observation b8bab20d-dde3-438b-8996-3bc7c1686bc6 · outbound

This paper cites Riegler, and Vajira Thambawita.

Data Augmentation with Diffusion Models for Colon Polyp Localization on the Low Data Regime: How much real data is enough? Riegler, and Vajira Thambawita

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:49:00.739635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T10:49:00.556338Z digest=sha256:27f890752b018b7e18ff15c5088a11e117bfd8b0ae941c19f3d122704b3a1251

Observation 47ef9fda-c9c5-4082-a794-721c2c276474 · outbound

This paper cites Development of a computer-aided detection system for colonoscopy and a publicly accessible large colonoscopy video database (with video).

Data Augmentation with Diffusion Models for Colon Polyp Localization on the Low Data Regime: How much real data is enough? Development of a computer-aided detection system for colonoscopy and a publicly accessible large colonoscopy video database (with video)

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:49:00.730536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T10:49:00.559230Z digest=sha256:cd8350d3a92bb0bde7e1527f91248a5df149cb826a4709ab5f4e1cf663c92bb0

Observation ef9061fe-89e9-48f5-98a4-74458eadd7b8 · outbound

This paper cites Repolyp: A framework for generating realistic colon polyps with corresponding segmentation masks using diffusion models.

Data Augmentation with Diffusion Models for Colon Polyp Localization on the Low Data Regime: How much real data is enough? Repolyp: A framework for generating realistic colon polyps with corresponding segmentation masks using diffusion models

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:49:00.721459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T10:49:00.562177Z digest=sha256:cdad53feee5e097d7955a2ec74c251622969379b5d325b9b90e505ec851f96a5

Observation 9faba026-8a04-4b37-bfda-57846ccae981 · outbound

This paper cites Sdxl: Improving latent diffusion models for high-resolution image synthesis, 2023.

Data Augmentation with Diffusion Models for Colon Polyp Localization on the Low Data Regime: How much real data is enough? Sdxl: Improving latent diffusion models for high-resolution image synthesis, 2023

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-12T10:49:00.565259Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:49:00.565259Z digest=sha256:0c48cf3fd4887c7da15de0c3c2781ab9f59d7bcc8d72794b27649590f66e7651

Observation b1c64038-b4dd-40bd-8017-0e606805b49b · outbound

This paper cites Kvasir: A multi-class image dataset for computer aided gastrointestinal disease detection.

Data Augmentation with Diffusion Models for Colon Polyp Localization on the Low Data Regime: How much real data is enough? Kvasir: A multi-class image dataset for computer aided gastrointestinal disease detection

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:49:00.707380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T10:49:00.568139Z digest=sha256:c6146c540cefa444ebad649bbba2b0a7d428c793148f7b71722486b6757b3e81

Observation abcb2c32-bace-44b6-a63d-101834a5d595 · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

Data Augmentation with Diffusion Models for Colon Polyp Localization on the Low Data Regime: How much real data is enough? High-resolution image synthesis with latent diffusion models

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:49:00.696951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T10:49:00.571043Z digest=sha256:d9b3bbaa2d75a12299778036dc26022f156a887fd0ac05544ca7c2094983644f

Observation e8a84313-e612-4827-98aa-559148f129d0 · outbound

This paper cites Laion-5b: An open large-scale dataset for training next generation image-text models.

Data Augmentation with Diffusion Models for Colon Polyp Localization on the Low Data Regime: How much real data is enough? Laion-5b: An open large-scale dataset for training next generation image-text models

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:49:00.687437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T10:49:00.573774Z digest=sha256:384db7f60a5891f9dd77be48efd99250cb69e28acf6e5adb39c6e0a801677223

Observation 69eadb32-f3e2-4557-bc43-c7a01c87f92f · outbound

This paper cites To- ward embedded detection of polyps in wce images for early diagnosis of colorectal cancer.

Data Augmentation with Diffusion Models for Colon Polyp Localization on the Low Data Regime: How much real data is enough? To- ward embedded detection of polyps in wce images for early diagnosis of colorectal cancer

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:49:00.677355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T10:49:00.576795Z digest=sha256:2715accc72c81f9a85756a7d29b98c5a13ac0b633fbb7c8b2d6e072a92771add

Observation e27718b0-3383-4911-a3f4-a805ce0a9041 · outbound

This paper cites Understanding and mitigating copying in diffusion models.

Data Augmentation with Diffusion Models for Colon Polyp Localization on the Low Data Regime: How much real data is enough? Understanding and mitigating copying in diffusion models

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-12T10:49:00.579935Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:49:00.579935Z digest=sha256:d49a83fa0af0cd5b49880ca364f5bc84a1bea76e7cd17c2e4c0d4c948cf2ffc5

Observation 2bef6bc9-99c7-44be-b101-15731c84d21b · outbound

This paper cites Yolov9: Learning what you want to learn using programmable gradient information, 2024.

Data Augmentation with Diffusion Models for Colon Polyp Localization on the Low Data Regime: How much real data is enough? Yolov9: Learning what you want to learn using programmable gradient information, 2024

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:49:00.663828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T10:49:00.582934Z digest=sha256:9523532007eec4d73fd232b82e916fc4afc0a1558d1ba0f5b84f8077a8f53a3e

Observation fb392822-1c37-47e4-87f0-7a44d881d6f2 · outbound

This paper cites Cutmix: Regularization strategy to train strong classifiers with local- izable features.

Data Augmentation with Diffusion Models for Colon Polyp Localization on the Low Data Regime: How much real data is enough? Cutmix: Regularization strategy to train strong classifiers with local- izable features

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:49:00.654741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T10:49:00.585931Z digest=sha256:503cbb461aca62066463971e006b2e3270e6512c45d40b7c917496ec6de052b2

Observation 5a938033-a67c-4e1a-a9d5-b12c37cf7336 · outbound

This paper cites Expanding Small-Scale Datasets with Guided Imagination.

Data Augmentation with Diffusion Models for Colon Polyp Localization on the Low Data Regime: How much real data is enough? Expanding Small-Scale Datasets with Guided Imagination

Reference 27

Resolution
verified exact
local_arxiv, observed 2026-08-12T10:49:00.615831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T10:49:00.589469Z digest=sha256:a6c6f79bd5e0dbc5767818c06ff31fe78ce2c895a100ff1996a0932046df859c

Pith citing papers

No inbound Pith citation observations are available.