Paper Citation Record · LEDGER

Grounding Multimodal Large Language Models with Quantitative Skin Attributes: A Retrieval Study

As of 10 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2508.20188.

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

pith.paper-citation-record.v1
2508.20188 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T15:18:46.209624Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

24 of 24 outbound references displayed

verified exact1
verified fuzzy14
unresolved9
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c91005ca-6987-4f4c-9641-6d12bc93fcf0 · outbound

This paper cites MedImageInsight: An Open-Source Embedding Model for General Domain Medical Imaging.

Grounding Multimodal Large Language Models with Quantitative Skin Attributes: A Retrieval Study MedImageInsight: An Open-Source Embedding Model for General Domain Medical Imaging

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-05T15:18:44.377415Z

Source-reported events for the cited work

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Observation b0b28e8d-3d76-440c-8f9e-27eeb4d521ec · outbound

This paper cites Validation of artificial intelligence prediction models for skin cancer diagnosis using dermoscopy images: the 2019 international skin imaging collaboration grand challenge.

Grounding Multimodal Large Language Models with Quantitative Skin Attributes: A Retrieval Study Validation of artificial intelligence prediction models for skin cancer diagnosis using dermoscopy images: the 2019 international skin imaging collaboration grand challenge

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:18:49.080855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e79d4228-dae4-4244-9455-8673d2e8745c · outbound

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

Grounding Multimodal Large Language Models with Quantitative Skin Attributes: A Retrieval Study An image is worth 16x16 words: Transformers for image recognition at scale

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-05T15:18:44.544462Z

Source-reported events for the cited work

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Observation 5a16eecf-1504-447a-8fa7-1edfd031d9ce · outbound

This paper cites Analysis of trends in geographic distribution of us dermatology workforce density.

Grounding Multimodal Large Language Models with Quantitative Skin Attributes: A Retrieval Study Analysis of trends in geographic distribution of us dermatology workforce density

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:18:48.831526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 933d7108-5a32-45fa-a79d-ddecd706221b · outbound

This paper cites LoRA: Low-rank adaptation of large language models.

Grounding Multimodal Large Language Models with Quantitative Skin Attributes: A Retrieval Study LoRA: Low-rank adaptation of large language models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-05T15:18:44.684834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1983dd57-45d5-400c-aedb-0c3c9b4f10e5 · outbound

This paper cites Transparent medical image ai via an image–text foundation model grounded in medical literature.

Grounding Multimodal Large Language Models with Quantitative Skin Attributes: A Retrieval Study Transparent medical image ai via an image–text foundation model grounded in medical literature

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:18:48.588042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 27d36465-a168-496c-8511-8e2f48e32d3b · outbound

This paper cites Human-ai interaction in skin cancer diagnosis: a systematic review and meta-analysis.

Grounding Multimodal Large Language Models with Quantitative Skin Attributes: A Retrieval Study Human-ai interaction in skin cancer diagnosis: a systematic review and meta-analysis

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:18:48.428291Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a3fee907-6528-46d1-a91f-5d3aac03d17a · outbound

This paper cites The slice-3d dataset: 400,000 skin lesion image crops extracted from 3d tbp for skin cancer detection.

Grounding Multimodal Large Language Models with Quantitative Skin Attributes: A Retrieval Study The slice-3d dataset: 400,000 skin lesion image crops extracted from 3d tbp for skin cancer detection

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:18:48.172329Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c931a68e-0be6-483a-b49d-4896618de5bf · outbound

This paper cites Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models.

Grounding Multimodal Large Language Models with Quantitative Skin Attributes: A Retrieval Study Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-05T15:18:45.014349Z

Source-reported events for the cited work

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Observation 8478ded3-3bee-4586-9f57-563c5a983952 · outbound

This paper cites 3d whole-body skin imaging for automated melanoma detection.

Grounding Multimodal Large Language Models with Quantitative Skin Attributes: A Retrieval Study 3d whole-body skin imaging for automated melanoma detection

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:18:48.022744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation fb5e098f-c316-43cf-8753-15d5ed2c38b1 · outbound

This paper cites Learning transferable visual models from natural language supervision.

Grounding Multimodal Large Language Models with Quantitative Skin Attributes: A Retrieval Study Learning transferable visual models from natural language supervision

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:18:47.894507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e275ef87-4999-4481-954a-b740839a2537 · outbound

This paper cites Steering llama 2 via contrastive activation addition.

Grounding Multimodal Large Language Models with Quantitative Skin Attributes: A Retrieval Study Steering llama 2 via contrastive activation addition

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:18:47.719743Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 17bb9f56-093f-4dcb-b880-cf22a6bfcc39 · outbound

This paper cites Grad-cam: Visual explanations from deep networks via gradient-based localization.

Grounding Multimodal Large Language Models with Quantitative Skin Attributes: A Retrieval Study Grad-cam: Visual explanations from deep networks via gradient-based localization

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-05T15:18:45.416054Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d3e5c552-b236-4167-be21-716c29041771 · outbound

This paper cites Socioeconomic and geographic barriers to dermatology care in urban and rural us populations.

Grounding Multimodal Large Language Models with Quantitative Skin Attributes: A Retrieval Study Socioeconomic and geographic barriers to dermatology care in urban and rural us populations

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:18:47.508759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b55f806f-f8ff-45cb-b12e-1bb749c356bc · outbound

This paper cites Composing text and image for image retrieval-an empirical odyssey.

Grounding Multimodal Large Language Models with Quantitative Skin Attributes: A Retrieval Study Composing text and image for image retrieval-an empirical odyssey

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:18:47.360891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 83d6baf8-9c44-4186-b411-733ac619071d · outbound

This paper cites Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution.

Grounding Multimodal Large Language Models with Quantitative Skin Attributes: A Retrieval Study Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-05T15:18:45.626372Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 49e3d848-5bca-4379-ba46-518088999649 · outbound

This paper cites VisNumBench: Evaluating Number Sense of Multimodal Large Language Models.

Grounding Multimodal Large Language Models with Quantitative Skin Attributes: A Retrieval Study VisNumBench: Evaluating Number Sense of Multimodal Large Language Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-05T15:18:45.699326Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1b61aaa9-76cf-41ff-9db0-539acd98ffeb · outbound

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

Grounding Multimodal Large Language Models with Quantitative Skin Attributes: A Retrieval Study Derm1M: A Million-scale Vision-Language Dataset Aligned with Clinical Ontology Knowledge for Dermatology

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-05T15:18:45.769309Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b776e1cc-ef69-4b29-8767-f9e37f939b3b · outbound

This paper cites A multimodal vision foundation model for clinical dermatology.

Grounding Multimodal Large Language Models with Quantitative Skin Attributes: A Retrieval Study A multimodal vision foundation model for clinical dermatology

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:18:47.196661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 6b2d822d-bf12-435f-bb7f-beb71bf363eb · outbound

This paper cites Qwen2 Technical Report.

Grounding Multimodal Large Language Models with Quantitative Skin Attributes: A Retrieval Study Qwen2 Technical Report

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-05T15:18:45.884802Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 177cd5a3-b2db-4ad6-8b59-acf93633a55f · outbound

This paper cites Visrag: Vision-based retrieval-augmented generation on multi-modality documents.

Grounding Multimodal Large Language Models with Quantitative Skin Attributes: A Retrieval Study Visrag: Vision-based retrieval-augmented generation on multi-modality documents

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:18:46.973569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 49f59181-aba5-4486-86a5-4641af924ae8 · outbound

This paper cites MM-Skin: Enhancing Dermatology Vision-Language Model with an Image-Text Dataset Derived from Textbooks.

Grounding Multimodal Large Language Models with Quantitative Skin Attributes: A Retrieval Study MM-Skin: Enhancing Dermatology Vision-Language Model with an Image-Text Dataset Derived from Textbooks

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-08-05T15:18:46.381344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2a98d987-e749-44ef-a093-65e209631c1c · outbound

This paper cites Revisiting the trustworthiness of saliency methods in radiology ai.

Grounding Multimodal Large Language Models with Quantitative Skin Attributes: A Retrieval Study Revisiting the trustworthiness of saliency methods in radiology ai

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:18:46.821178Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a19ca186-d62a-46ee-b73c-647881d6bf97 · outbound

This paper cites Pre-trained multimodal large language model enhances dermatological diagnosis using skingpt-4.

Grounding Multimodal Large Language Models with Quantitative Skin Attributes: A Retrieval Study Pre-trained multimodal large language model enhances dermatological diagnosis using skingpt-4

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:18:46.651647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Pith citing papers

No inbound Pith citation observations are available.