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Paper Citation Record · LEDGER

MAKE: Multi-Aspect Knowledge-Enhanced Vision-Language Pretraining for Zero-shot Dermatological Assessment

As of 22 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 1 inbound Pith citation observation for arXiv:2505.09372.

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

pith.paper-citation-record.v1
2505.09372 v1

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:37:40.301855Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-15T02:56:04.280700Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

29 of 29 outbound references displayed

  • verified exact0
  • verified fuzzy8
  • unresolved20
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External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 49e5b089-45fa-432d-afe4-b2ee62ea2497 · outbound

This paper cites Advances in Neural Information Processing Systems35, 18157–18167 (2022).

MAKE: Multi-Aspect Knowledge-Enhanced Vision-Language Pretraining for Zero-shot Dermatological Assessment Advances in Neural Information Processing Systems35, 18157–18167 (2022)

Reference 1

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Source-reported events for the cited work

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Observation 09cdfc4d-a793-4222-aa77-d8de1c026c8e · outbound

This paper cites an unresolved cited work.

MAKE: Multi-Aspect Knowledge-Enhanced Vision-Language Pretraining for Zero-shot Dermatological Assessment Unresolved cited work

Reference 2

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Source-reported events for the cited work

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Observation c15ca01f-0393-4951-8ee3-e461a2467391 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

MAKE: Multi-Aspect Knowledge-Enhanced Vision-Language Pretraining for Zero-shot Dermatological Assessment An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 3

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Observation 25232931-1b77-4615-9242-7336697895b0 · outbound

This paper cites nature 542(7639), 115–118 (2017).

MAKE: Multi-Aspect Knowledge-Enhanced Vision-Language Pretraining for Zero-shot Dermatological Assessment nature 542(7639), 115–118 (2017)

Reference 4

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no resolver link, observed 2026-08-15T21:37:40.186656Z

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Observation ff98473b-b738-4447-bc14-1b25961401fa · outbound

This paper cites Advances in Neural Information Processing Systems36, 35544– 35575 (2023).

MAKE: Multi-Aspect Knowledge-Enhanced Vision-Language Pretraining for Zero-shot Dermatological Assessment Advances in Neural Information Processing Systems36, 35544– 35575 (2023)

Reference 5

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Observation 97ff7a92-3f55-43c6-bb60-27808788b7a5 · outbound

This paper cites In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.

MAKE: Multi-Aspect Knowledge-Enhanced Vision-Language Pretraining for Zero-shot Dermatological Assessment In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

Reference 6

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Unavailable: canonical work link unavailable.

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Observation 66cbf5ef-beb9-4c03-90ac-2ff143ab6d58 · outbound

This paper cites https://doi.org/10.6084/m9.figshare.6454973.v12.

MAKE: Multi-Aspect Knowledge-Enhanced Vision-Language Pretraining for Zero-shot Dermatological Assessment https://doi.org/10.6084/m9.figshare.6454973.v12

Reference 7

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Observation ed3262a7-c467-49bd-bfb1-4b180592d697 · outbound

This paper cites OphCLIP: Hierarchical Retrieval-Augmented Learning for Ophthalmic Surgical Video-Language Pretraining.

MAKE: Multi-Aspect Knowledge-Enhanced Vision-Language Pretraining for Zero-shot Dermatological Assessment OphCLIP: Hierarchical Retrieval-Augmented Learning for Ophthalmic Surgical Video-Language Pretraining

Reference 8

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Observation d11b5144-5691-41a8-82c7-31763b0448f1 · outbound

This paper cites Advances in neural information processing systems36, 37995– 38017 (2023).

MAKE: Multi-Aspect Knowledge-Enhanced Vision-Language Pretraining for Zero-shot Dermatological Assessment Advances in neural information processing systems36, 37995– 38017 (2023)

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 591c8aa8-c17f-4fae-966b-4a63b849cf4a · outbound

This paper cites In: Proceedings of the AAAI conference on artificial intelligence.

MAKE: Multi-Aspect Knowledge-Enhanced Vision-Language Pretraining for Zero-shot Dermatological Assessment In: Proceedings of the AAAI conference on artificial intelligence

Reference 10

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Observation ed56b0e1-3fd0-4ff9-9a2d-8fba49d09ce6 · outbound

This paper cites Scientific data 6(1), 317 (2019) 10 Authors Suppressed Due to Excessive Length.

MAKE: Multi-Aspect Knowledge-Enhanced Vision-Language Pretraining for Zero-shot Dermatological Assessment Scientific data 6(1), 317 (2019) 10 Authors Suppressed Due to Excessive Length

Reference 11

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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 2026-08-22T06:32:14.747728+00:00.

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Observation 8f8691ac-3231-46dc-a066-4096140b0ff5 · outbound

This paper cites IEEE Journal of Biomedical and Health Informatics 23(2), 538–546 (mar 2019).

MAKE: Multi-Aspect Knowledge-Enhanced Vision-Language Pretraining for Zero-shot Dermatological Assessment IEEE Journal of Biomedical and Health Informatics 23(2), 538–546 (mar 2019)

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation b7dd9492-648d-4e3d-91a8-43b8a0659419 · outbound

This paper cites Nature Medicine30(4), 1154–1165 (2024).

MAKE: Multi-Aspect Knowledge-Enhanced Vision-Language Pretraining for Zero-shot Dermatological Assessment Nature Medicine30(4), 1154–1165 (2024)

Reference 13

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Observation 94f8b3d0-3e9b-45c4-a052-155c0eaee52c · outbound

This paper cites In: International Conference on Medical Image Computing and Computer-Assisted Intervention.

MAKE: Multi-Aspect Knowledge-Enhanced Vision-Language Pretraining for Zero-shot Dermatological Assessment In: International Conference on Medical Image Computing and Computer-Assisted Intervention

Reference 14

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Observation 9bc592b7-fd87-4f5b-8f0d-3b4e66557b0f · outbound

This paper cites Nature medicine26(6), 900–908 (2020).

MAKE: Multi-Aspect Knowledge-Enhanced Vision-Language Pretraining for Zero-shot Dermatological Assessment Nature medicine26(6), 900–908 (2020)

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 0d598655-d3b6-461a-aff7-cd04c7af30cd · outbound

This paper cites Data in Brief32, 106221 (2020).

MAKE: Multi-Aspect Knowledge-Enhanced Vision-Language Pretraining for Zero-shot Dermatological Assessment Data in Brief32, 106221 (2020)

Reference 16

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation ea684d12-a8dc-4c7c-8f7e-bd7a624debb5 · outbound

This paper cites In: International conference on machine learning.

MAKE: Multi-Aspect Knowledge-Enhanced Vision-Language Pretraining for Zero-shot Dermatological Assessment In: International conference on machine learning

Reference 17

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Source-reported events for the cited work

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Observation 98a5d8e3-30b3-4cd0-88e1-c62ab1dd4f4c · outbound

This paper cites OpenAI blog1(8), 9 (2019).

MAKE: Multi-Aspect Knowledge-Enhanced Vision-Language Pretraining for Zero-shot Dermatological Assessment OpenAI blog1(8), 9 (2019)

Reference 18

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Observation 4d1209f3-2d47-4d72-a024-772a86c05146 · outbound

This paper cites NPJ Digital Medicine7(1), 28 (2024).

MAKE: Multi-Aspect Knowledge-Enhanced Vision-Language Pretraining for Zero-shot Dermatological Assessment NPJ Digital Medicine7(1), 28 (2024)

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 9d03d7a2-2f05-4ddb-9a9a-0e2e45fce610 · outbound

This paper cites In: Leibe, B., Matas, J., Sebe, N., Welling, M.

MAKE: Multi-Aspect Knowledge-Enhanced Vision-Language Pretraining for Zero-shot Dermatological Assessment In: Leibe, B., Matas, J., Sebe, N., Welling, M

Reference 20

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation f5cbd1bd-5f49-423e-81cb-b1d443b6e4f2 · outbound

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MAKE: Multi-Aspect Knowledge-Enhanced Vision-Language Pretraining for Zero-shot Dermatological Assessment Unresolved cited work

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 9b9737a7-5245-4e06-98a2-a62959330480 · outbound

This paper cites Derm1M: A Million-scale Vision-Language Dataset Aligned with Clinical Ontology Knowledge for Dermatology.

MAKE: Multi-Aspect Knowledge-Enhanced Vision-Language Pretraining for Zero-shot Dermatological Assessment Derm1M: A Million-scale Vision-Language Dataset Aligned with Clinical Ontology Knowledge for Dermatology

Reference 22

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Observation 19ae218d-ddff-4a8d-80da-95e9dbb34e5f · outbound

This paper cites A Multimodal Vision Foundation Model for Clinical Dermatology.

MAKE: Multi-Aspect Knowledge-Enhanced Vision-Language Pretraining for Zero-shot Dermatological Assessment A Multimodal Vision Foundation Model for Clinical Dermatology

Reference 23

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Observation af171fdc-69e6-46d3-aa91-dd78b420c24c · outbound

This paper cites In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.

MAKE: Multi-Aspect Knowledge-Enhanced Vision-Language Pretraining for Zero-shot Dermatological Assessment In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

Reference 24

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation c437a4de-d01f-4f7f-9099-4d3bc1a178d6 · outbound

This paper cites CoCa: Contrastive Captioners are Image-Text Foundation Models.

MAKE: Multi-Aspect Knowledge-Enhanced Vision-Language Pretraining for Zero-shot Dermatological Assessment CoCa: Contrastive Captioners are Image-Text Foundation Models

Reference 25

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Observation d3e4e2fd-b138-4435-9265-21748441e0de · outbound

This paper cites In: Proceedings of the IEEE/CVF international conference on computer vision.

MAKE: Multi-Aspect Knowledge-Enhanced Vision-Language Pretraining for Zero-shot Dermatological Assessment In: Proceedings of the IEEE/CVF international conference on computer vision

Reference 26

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation eaf2a880-1834-4eb2-8770-35433b4cd474 · outbound

This paper cites BiomedCLIP: a multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairs.

MAKE: Multi-Aspect Knowledge-Enhanced Vision-Language Pretraining for Zero-shot Dermatological Assessment BiomedCLIP: a multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairs

Reference 27

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Unavailable: canonical work link unavailable.

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Observation 938b4bd6-edb4-4a3c-97c5-b7d45d6026d3 · outbound

This paper cites In: European Conference on Computer Vision.

MAKE: Multi-Aspect Knowledge-Enhanced Vision-Language Pretraining for Zero-shot Dermatological Assessment In: European Conference on Computer Vision

Reference 28

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation a4309365-4397-4d02-9cf7-851b77df5735 · outbound

This paper cites arXiv preprint arXiv:2405.18004 (2024).

MAKE: Multi-Aspect Knowledge-Enhanced Vision-Language Pretraining for Zero-shot Dermatological Assessment arXiv preprint arXiv:2405.18004 (2024)

Reference 29

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Pith citing papers

Observation 810552e2-bd09-49af-b4b6-fb7022a83d7f · inbound

DermAgent: A Self-Reflective Agentic System for Dermatological Image Analysis with Multi-Tool Reasoning and Traceable Decision-Making cites this paper.

DermAgent: A Self-Reflective Agentic System for Dermatological Image Analysis with Multi-Tool Reasoning and Traceable Decision-Making MAKE: Multi-Aspect Knowledge-Enhanced Vision-Language Pretraining for Zero-shot Dermatological Assessment

Reference 28

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arxiv_id, observed 2026-05-15T02:58:33.483609Z

Source-reported events for the cited work

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