Paper Citation Record · LEDGER

Beyond Pixel Agreement: Large Language Models as Clinical Guardrails for Reliable Medical Image Segmentation

As of 19 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2506.01841.

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

pith.paper-citation-record.v1
2506.01841 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:37:02.212362Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+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

32 of 32 outbound references displayed

verified exact2
verified fuzzy20
unresolved10
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0e7a1b6c-f40a-4c50-ae55-2d9404184e17 · outbound

This paper cites WeGA: Weakly-Supervised Global-Local Affinity Learning Framework for Lymph Node Metastasis Prediction in Rectal Cancer.

Beyond Pixel Agreement: Large Language Models as Clinical Guardrails for Reliable Medical Image Segmentation WeGA: Weakly-Supervised Global-Local Affinity Learning Framework for Lymph Node Metastasis Prediction in Rectal Cancer

Reference 1

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Observation 1729bf7f-a586-479c-a4c3-75ae19594490 · outbound

This paper cites Multi-modal disease segmentation with continual learning and adaptive decision fusion.

Beyond Pixel Agreement: Large Language Models as Clinical Guardrails for Reliable Medical Image Segmentation Multi-modal disease segmentation with continual learning and adaptive decision fusion

Reference 2

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Observation 80eb8898-ee3b-4a87-9005-42805eb33ba2 · outbound

This paper cites Tooth instance segmentation and disease detection with uncertainty-aware contrastive learning and cross-scale attention.

Beyond Pixel Agreement: Large Language Models as Clinical Guardrails for Reliable Medical Image Segmentation Tooth instance segmentation and disease detection with uncertainty-aware contrastive learning and cross-scale attention

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:37:02.554398Z

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Observation d5538723-24dd-4e76-93aa-e68a5c1eb1f3 · outbound

This paper cites Transmed: Transformers advance multi-modal medical image classification.

Beyond Pixel Agreement: Large Language Models as Clinical Guardrails for Reliable Medical Image Segmentation Transmed: Transformers advance multi-modal medical image classification

Reference 4

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Observation 7e67cabe-ab39-4bf8-be34-77ee74fced5a · outbound

This paper cites Facial video-based non- contact stress recognition utilizing multi-task learning with peak attention.

Beyond Pixel Agreement: Large Language Models as Clinical Guardrails for Reliable Medical Image Segmentation Facial video-based non- contact stress recognition utilizing multi-task learning with peak attention

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:37:02.540565Z

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Observation f7aced4c-f919-4d9b-9cfb-7661f398ced0 · outbound

This paper cites An anatomy-aware framework for automatic segmentation of parotid tumor from multimodal mri.

Beyond Pixel Agreement: Large Language Models as Clinical Guardrails for Reliable Medical Image Segmentation An anatomy-aware framework for automatic segmentation of parotid tumor from multimodal mri

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:37:02.531336Z

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Observation a3747f31-1668-4880-810a-dee0abdccd6b · outbound

This paper cites Desam: Decoupled segment anything model for generalizable medical image segmentation.

Beyond Pixel Agreement: Large Language Models as Clinical Guardrails for Reliable Medical Image Segmentation Desam: Decoupled segment anything model for generalizable medical image segmentation

Reference 7

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Observation 4df88c99-d5d4-4a50-ac3f-82c8e43d91a0 · outbound

This paper cites Mba-net: Sam-driven bidirec- tional aggregation network for ovarian tumor segmentation.

Beyond Pixel Agreement: Large Language Models as Clinical Guardrails for Reliable Medical Image Segmentation Mba-net: Sam-driven bidirec- tional aggregation network for ovarian tumor segmentation

Reference 8

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Observation 0a9a2d75-4d90-411a-99b6-091d06f2bfaf · outbound

This paper cites Abs-mamba: Sam2-driven bidirectional spiral mamba network for medical image translation.

Beyond Pixel Agreement: Large Language Models as Clinical Guardrails for Reliable Medical Image Segmentation Abs-mamba: Sam2-driven bidirectional spiral mamba network for medical image translation

Reference 9

Resolution: verified exact; raw_fallback, observed 2026-08-07T11:37:02.325218Z

Source-reported events for the cited work

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Observation 6773e2c8-5a50-4ebd-b0b4-0cf81a38ea21 · outbound

This paper cites Medical image segmentation review: The suc- cess of u-net.

Beyond Pixel Agreement: Large Language Models as Clinical Guardrails for Reliable Medical Image Segmentation Medical image segmentation review: The suc- cess of u-net

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:37:02.507706Z

Source-reported events for the cited work

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Observation 9a7c15ac-4b29-4c4b-87fa-701e88794dcc · outbound

This paper cites Qualitative evaluation of common quantitative metrics for clinical acceptance of automatic segmentation: a case study on heart contouring from ct images by deep learning algorithms.

Beyond Pixel Agreement: Large Language Models as Clinical Guardrails for Reliable Medical Image Segmentation Qualitative evaluation of common quantitative metrics for clinical acceptance of automatic segmentation: a case study on heart contouring from ct images by deep learning algorithms

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:37:02.499244Z

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Observation f97b1479-25e2-483e-96ee-78a3990ac8fa · outbound

This paper cites No-reference seg- mentation annotation quality assessment.

Beyond Pixel Agreement: Large Language Models as Clinical Guardrails for Reliable Medical Image Segmentation No-reference seg- mentation annotation quality assessment

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:37:02.489780Z

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Observation 22b624f3-aef7-4dd2-bf1c-836ce35ae6fa · outbound

This paper cites Medical image segmentation automatic quality control: A multi- dimensional approach.

Beyond Pixel Agreement: Large Language Models as Clinical Guardrails for Reliable Medical Image Segmentation Medical image segmentation automatic quality control: A multi- dimensional approach

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:37:02.480358Z

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Observation dd2687d4-a594-4912-a4d8-ff0d8916e08f · outbound

This paper cites SQA-SAM: Segmentation Quality Assessment for Medical Images Utilizing the Segment Anything Model.

Beyond Pixel Agreement: Large Language Models as Clinical Guardrails for Reliable Medical Image Segmentation SQA-SAM: Segmentation Quality Assessment for Medical Images Utilizing the Segment Anything Model

Reference 14

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Observation 380962c2-55a6-4141-9cea-f10e7701d9b8 · outbound

This paper cites A robust quality estimation method for medical image segmentation with small datasets.

Beyond Pixel Agreement: Large Language Models as Clinical Guardrails for Reliable Medical Image Segmentation A robust quality estimation method for medical image segmentation with small datasets

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:37:02.471551Z

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Observation 3deed07d-a769-43c9-bfeb-f60fd09234b0 · outbound

This paper cites Segmentation quality assessment by automated detection of erroneous surface regions in medical images.

Beyond Pixel Agreement: Large Language Models as Clinical Guardrails for Reliable Medical Image Segmentation Segmentation quality assessment by automated detection of erroneous surface regions in medical images

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:37:02.462391Z

Source-reported events for the cited work

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Observation 7947a234-b50f-494e-bae8-601805961ca9 · outbound

This paper cites Trustworthy clinical ai solutions: A unified review of uncertainty quantifi- cation in deep learning models for medical image analysis.

Beyond Pixel Agreement: Large Language Models as Clinical Guardrails for Reliable Medical Image Segmentation Trustworthy clinical ai solutions: A unified review of uncertainty quantifi- cation in deep learning models for medical image analysis

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:37:02.453293Z

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Observation 2b6f7c3e-a7a8-4e99-b608-c5b549ac6aff · outbound

This paper cites Efficient bayesian uncertainty estimation for nnu-net.

Beyond Pixel Agreement: Large Language Models as Clinical Guardrails for Reliable Medical Image Segmentation Efficient bayesian uncertainty estimation for nnu-net

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:37:02.443670Z

Source-reported events for the cited work

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Observation 376b4a1a-f577-4acc-9ed7-18633d1573fa · outbound

This paper cites Quality Sentinel: Estimating Label Quality and Errors in Medical Segmentation Datasets.

Beyond Pixel Agreement: Large Language Models as Clinical Guardrails for Reliable Medical Image Segmentation Quality Sentinel: Estimating Label Quality and Errors in Medical Segmentation Datasets

Reference 19

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Observation 20ed0486-1d52-4c69-a624-0dbebf84c5c6 · outbound

This paper cites A survey on evaluation of large language models.

Beyond Pixel Agreement: Large Language Models as Clinical Guardrails for Reliable Medical Image Segmentation A survey on evaluation of large language models

Reference 20

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Observation 1050a3f2-ed5d-47a5-8b9d-47e878ac089b · outbound

This paper cites Large language models in medicine.

Beyond Pixel Agreement: Large Language Models as Clinical Guardrails for Reliable Medical Image Segmentation Large language models in medicine

Reference 21

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Observation f76589b7-e619-4b9e-94b4-f37bc062229f · outbound

This paper cites Application of large language models in medicine.

Beyond Pixel Agreement: Large Language Models as Clinical Guardrails for Reliable Medical Image Segmentation Application of large language models in medicine

Reference 22

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Observation be4639f6-0f4d-4e92-a2ce-fefb2b1a7890 · outbound

This paper cites Gpt-4v (ision) is a human-aligned evaluator for text-to-3d generation.

Beyond Pixel Agreement: Large Language Models as Clinical Guardrails for Reliable Medical Image Segmentation Gpt-4v (ision) is a human-aligned evaluator for text-to-3d generation

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:37:02.417983Z

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Observation 8b25a40c-b80d-4d0f-9723-3a7e0383d5e4 · outbound

This paper cites Multimodal large language models address clinical queries in laryngeal cancer surgery: a com- parative evaluation of image interpretation across different models.

Beyond Pixel Agreement: Large Language Models as Clinical Guardrails for Reliable Medical Image Segmentation Multimodal large language models address clinical queries in laryngeal cancer surgery: a com- parative evaluation of image interpretation across different models

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:37:02.408625Z

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Observation 25774fd4-8512-434d-ab57-525ec3abb4cf · outbound

This paper cites Bliva: A simple multimodal llm for better handling of text-rich visual questions.

Beyond Pixel Agreement: Large Language Models as Clinical Guardrails for Reliable Medical Image Segmentation Bliva: A simple multimodal llm for better handling of text-rich visual questions

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:37:02.398846Z

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Observation f7d34442-0061-4409-8054-05efd2b43374 · outbound

This paper cites Large language models are latent variable models: Explaining and find- ing good demonstrations for in-context learning.

Beyond Pixel Agreement: Large Language Models as Clinical Guardrails for Reliable Medical Image Segmentation Large language models are latent variable models: Explaining and find- ing good demonstrations for in-context learning

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:37:02.390325Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 44f6468c-c1d5-481e-991f-8d1b917b4b95 · outbound

This paper cites Prompt engineering in consistency and reliability with the evidence- based guideline for llms.

Beyond Pixel Agreement: Large Language Models as Clinical Guardrails for Reliable Medical Image Segmentation Prompt engineering in consistency and reliability with the evidence- based guideline for llms

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:37:02.381051Z

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Observation e43fcdc2-ab1c-4381-b2ec-c148eadc08a3 · outbound

This paper cites Ai-generated annotations dataset for diverse cancer radiol- ogy collections in nci image data commons.

Beyond Pixel Agreement: Large Language Models as Clinical Guardrails for Reliable Medical Image Segmentation Ai-generated annotations dataset for diverse cancer radiol- ogy collections in nci image data commons

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:37:02.371954Z

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Observation 9d072df3-0bab-464d-b58c-528f994bf0ec · outbound

This paper cites nnu-net: a self-configuring method for deep learning-based biomedical image segmentation.

Beyond Pixel Agreement: Large Language Models as Clinical Guardrails for Reliable Medical Image Segmentation nnu-net: a self-configuring method for deep learning-based biomedical image segmentation

Reference 29

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Observation bf7e1e2a-363e-4d46-8e4f-f8a5e49d163d · outbound

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

Beyond Pixel Agreement: Large Language Models as Clinical Guardrails for Reliable Medical Image Segmentation Efficientnet: Rethinking model scaling for convolu- tional neural networks

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:37:02.358434Z

Source-reported events for the cited work

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Observation 4808135a-6bff-49c2-966b-c7eb38afbaf7 · outbound

This paper cites Deep residual learning for image recognition.

Beyond Pixel Agreement: Large Language Models as Clinical Guardrails for Reliable Medical Image Segmentation Deep residual learning for image recognition

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T11:37:02.209519Z

Source-reported events for the cited work

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Observation 20a8455d-18ae-4d86-9c78-bd7ef9d6a68c · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.

Beyond Pixel Agreement: Large Language Models as Clinical Guardrails for Reliable Medical Image Segmentation An image is worth 16x16 words: Transformers for image recognition at scale

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:37:02.344124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

No inbound Pith citation observations are available.