Paper Citation Record · LEDGER

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine

As of 8 August 2026, this Paper Citation Record lists 60 of 60 outbound references and 1 inbound Pith citation observation for arXiv:2508.02951.

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

pith.paper-citation-record.v1
2508.02951 v1

Coverage vector

measured 60 of 60 reference resolution

Typed states for the displayed outbound observations.

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measured 61 of 61 standing notices

One-hop event checks from named stored sources.

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measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T04:50:45.050116Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T04:50:45.808704Z

Reference resolution

60 of 60 outbound references displayed

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External citation measurements

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Outbound references

Observation 47c153a4-45ee-4a12-91f4-2dc59ba0543a · outbound

This paper cites MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine

Reference 1

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Observation 710b94de-7a56-4593-a1ca-35d63f90de9a · outbound

This paper cites These models combine text and image understanding and are typ- ically evaluated using visual question answering (VQA) tasks.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine These models combine text and image understanding and are typ- ically evaluated using visual question answering (VQA) tasks

Reference 2

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Observation 6af40122-e672-4103-8449-829ae1cbafde · outbound

This paper cites Perception enables clinicians to ex- tract key visual features before engaging in more complex 2 Figure 2.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine Perception enables clinicians to ex- tract key visual features before engaging in more complex 2 Figure 2

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:50:46.527645Z

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Observation e4d88d05-d7f5-42a3-9f80-f09ff5e32940 · outbound

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MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine Unresolved cited work

Reference 4

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Observation 847fb887-7ac6-46d8-bfa2-1993dbbd1d71 · outbound

This paper cites an unresolved cited work.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine Unresolved cited work

Reference 5

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Observation 7f86ac3c-fbac-475f-8c64-101e529991c7 · outbound

This paper cites an unresolved cited work.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine Unresolved cited work

Reference 6

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Observation 54d22850-cdf2-4baa-ae46-bf76d3454179 · outbound

This paper cites We mimic this form of prompting, by leveraging visual cues like points/dots to spatially prompt the models when answering the specified question [43, 50].

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine We mimic this form of prompting, by leveraging visual cues like points/dots to spatially prompt the models when answering the specified question [43, 50]

Reference 7

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Observation f0ade7de-781a-417f-b728-1541bb262b80 · outbound

This paper cites Current models including leading generalist and domain-specialized systems perform far below human levels on perceptual tasks that clinicians solve effortlessly (best: 65% vs.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine Current models including leading generalist and domain-specialized systems perform far below human levels on perceptual tasks that clinicians solve effortlessly (best: 65% vs

Reference 9

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Observation 6280ff95-d0ab-431c-bc7b-415cae1e46b7 · outbound

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MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine Unresolved cited work

Reference 11

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Observation d1fcc25d-bb44-4297-9949-9cef024da10d · outbound

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MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine Unresolved cited work

Reference 12

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Observation 382d428a-6816-4345-9815-1370576706e9 · outbound

This paper cites Small Specialized models We train small specialized models for some of the tasks with sizeable train sets from the original dataset used to construct the task.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine Small Specialized models We train small specialized models for some of the tasks with sizeable train sets from the original dataset used to construct the task

Reference 13

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Observation 29967050-21e7-49b3-b916-a48d40f29a5d · outbound

This paper cites Omnimedvqa: A new large- scale comprehensive evaluation benchmark for medical lvlm.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine Omnimedvqa: A new large- scale comprehensive evaluation benchmark for medical lvlm

Reference 26

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Observation 3fd89b40-4785-4f9c-9255-30b339a8010b · outbound

This paper cites GPT-4o System Card.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine GPT-4o System Card

Reference 27

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Observation f3429a48-d7ad-4bf8-9555-7e26f08a7c10 · outbound

This paper cites The diagnostic impact of contrast-enhanced computed tomography (cect) in evaluating lymph node involvement in colorectal cancer: a comprehen- sive review.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine The diagnostic impact of contrast-enhanced computed tomography (cect) in evaluating lymph node involvement in colorectal cancer: a comprehen- sive review

Reference 28

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Observation 4fa8b32c-08b4-4b95-8ee6-b032d571f42c · outbound

This paper cites Chexpert: A large chest radiograph dataset with uncertainty labels and expert comparison.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine Chexpert: A large chest radiograph dataset with uncertainty labels and expert comparison

Reference 29

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Observation 4702e604-2bdc-4114-abe0-c795ffa19983 · outbound

This paper cites A dataset of clinically generated visual questions and answers about radiology images.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine A dataset of clinically generated visual questions and answers about radiology images

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:50:46.346514Z

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Observation 42ef0246-05b1-41a5-90c1-25d056987509 · outbound

This paper cites Llava-onevision: Easy visual task transfer, 2024.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine Llava-onevision: Easy visual task transfer, 2024

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:50:46.328216Z

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Observation 8008b3fc-6a3b-4fff-87cd-a44e45d15971 · outbound

This paper cites LLaVA-OneVision: Easy Visual Task Transfer.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine LLaVA-OneVision: Easy Visual Task Transfer

Reference 32

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Observation 80da6ea6-1f71-466c-9550-417b77da3a1f · outbound

This paper cites Llava-med: Training a large language- and-vision assistant for biomedicine in one day.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine Llava-med: Training a large language- and-vision assistant for biomedicine in one day

Reference 33

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Observation 0f1634c8-b201-43e2-94db-5372c0df43d5 · outbound

This paper cites Slake: A semantically-labeled knowledge- enhanced dataset for medical visual question answering.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine Slake: A semantically-labeled knowledge- enhanced dataset for medical visual question answering

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:50:46.300661Z

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Observation 3039d259-df27-4083-9eb5-38244175a009 · outbound

This paper cites Improved Baselines with Visual Instruction Tuning.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine Improved Baselines with Visual Instruction Tuning

Reference 35

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Observation 503ad637-3270-4f14-acbd-35c7b1d9855a · outbound

This paper cites A Spectrum Evaluation Benchmark for Medical Multi-Modal Large Language Models.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine A Spectrum Evaluation Benchmark for Medical Multi-Modal Large Language Models

Reference 36

Resolution: verified exact; local_arxiv, observed 2026-08-06T04:50:45.737508Z

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Observation be03e375-8617-4b08-8dc6-5727ce900fe7 · outbound

This paper cites The coding of roentgen images for computer analysis as applied to lung cancer.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine The coding of roentgen images for computer analysis as applied to lung cancer

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:50:46.282228Z

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Observation b9d79b9d-06b9-4d12-a317-a8d6f17014b8 · outbound

This paper cites Lu, Bowen Chen, Drew F.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine Lu, Bowen Chen, Drew F

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:50:46.265144Z

Source-reported events for the cited work

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Observation 3fa64eb0-1fd8-4a7c-a042-bc6278f9868b · outbound

This paper cites Lung-rads: pushing the limits.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine Lung-rads: pushing the limits

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:50:46.246274Z

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Observation dca4a1ca-1a4c-4c61-89a8-22c858a68100 · outbound

This paper cites Towards Accurate Differential Diagnosis with Large Language Models.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine Towards Accurate Differential Diagnosis with Large Language Models

Reference 40

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Observation 4614b4aa-68e4-4136-8e44-eb087144fc66 · outbound

This paper cites Med-flamingo: a multimodal medical few-shot learner.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine Med-flamingo: a multimodal medical few-shot learner

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:50:46.229278Z

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Observation 7a1be3ce-2ba3-40d0-9881-1351627d55e9 · outbound

This paper cites Interactions of perceptual and conceptual pro- cessing: Expertise in medical image diagnosis.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine Interactions of perceptual and conceptual pro- cessing: Expertise in medical image diagnosis

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:50:46.212954Z

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Observation 0910e13e-2cab-4d99-92ef-3dbdd9f931a7 · outbound

This paper cites Beyond the Hype: A dispassionate look at vision-language models in medical scenario.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine Beyond the Hype: A dispassionate look at vision-language models in medical scenario

Reference 43

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Observation 3dbd8851-1a05-4103-8386-467712ece06c · outbound

This paper cites Video-based ai for beat-to-beat assessment of cardiac function.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine Video-based ai for beat-to-beat assessment of cardiac function

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:50:46.196722Z

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Observation bb599bb3-104d-4f89-b8eb-12d27c251d4f · outbound

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

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine Kvasir: A multi-class image dataset for computer aided gastrointestinal disease detection

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:50:46.177764Z

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Observation 4c63d650-f3ba-46a8-9471-4d7e92744df8 · outbound

This paper cites Learning transferable visual models from natural language supervision, 2021.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine Learning transferable visual models from natural language supervision, 2021

Reference 46

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Observation 95b409ea-16bb-41c5-9bbe-3c8adf40784d · outbound

This paper cites Mul- timedeval: A benchmark and a toolkit for evaluating medical vision-language models.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine Mul- timedeval: A benchmark and a toolkit for evaluating medical vision-language models

Reference 47

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Observation dbf45989-4f88-43f9-bbfb-004d4022d6f9 · outbound

This paper cites Hematoxylin and eosin-stained whole slide image dataset annotated for skin tissue segmentation.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine Hematoxylin and eosin-stained whole slide image dataset annotated for skin tissue segmentation

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:50:46.142357Z

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Observation cfd50d5a-86c3-4101-adee-4ff98f625024 · outbound

This paper cites MediConfusion: Can you trust your AI radiologist? Probing the reliability of multimodal medical foundation models.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine MediConfusion: Can you trust your AI radiologist? Probing the reliability of multimodal medical foundation models

Reference 49

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Observation 46cd4533-fb17-4e19-bb77-767cfc68408f · outbound

This paper cites Quilt-llava: Visual instruction tuning by extracting localized narratives from open-source histopathology videos.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine Quilt-llava: Visual instruction tuning by extracting localized narratives from open-source histopathology videos

Reference 50

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Observation 72043f7c-db68-416f-b52f-7337a3562546 · outbound

This paper cites Diagnostic ultrasound imaging: inside out.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine Diagnostic ultrasound imaging: inside out

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:50:46.102569Z

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Observation db8c5afb-1320-454f-9fe9-b77cbb2332d1 · outbound

This paper cites Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-06T04:50:45.249202Z

Source-reported events for the cited work

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Observation 66423372-b8a5-4212-9344-495965152d86 · outbound

This paper cites What clinicians want: contextualizing explainable machine learning for clinical end use.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine What clinicians want: contextualizing explainable machine learning for clinical end use

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:50:46.084094Z

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Observation 92afd454-277d-4b91-8d57-a9cbcf723d8f · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 54

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Observation f998d0a9-5378-44a1-8740-88c68dbde60a · outbound

This paper cites Corrado, Yossi Matias, Karan Singhal, Pete Florence, Alan Karthikesalingam, and Vivek Natarajan.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine Corrado, Yossi Matias, Karan Singhal, Pete Florence, Alan Karthikesalingam, and Vivek Natarajan

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:50:46.067523Z

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Observation 00bfc95d-4598-4802-a203-d9aea1a245c1 · outbound

This paper cites Baichuan-M1: Pushing the Medical Capability of Large Language Models.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine Baichuan-M1: Pushing the Medical Capability of Large Language Models

Reference 56

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Observation 0a69827b-6308-4eb3-9760-2852c2d11ef6 · outbound

This paper cites Chestx- ray8: Hospital-scale chest x-ray database and benchmarks on weakly-supervised classification and localization of common thorax diseases.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine Chestx- ray8: Hospital-scale chest x-ray database and benchmarks on weakly-supervised classification and localization of common thorax diseases

Reference 57

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Observation fd19d5cf-bcf1-4ea1-a4d5-e45f44bcb0ff · outbound

This paper cites Detection of radiographic abnor- malities in mammograms by means of optical scanning and computer analysis.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine Detection of radiographic abnor- malities in mammograms by means of optical scanning and computer analysis

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:50:46.040026Z

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Observation 12078155-60aa-4a78-b8e6-edd367152b85 · outbound

This paper cites Can GPT-4V(ision) Serve Medical Applications? Case Studies on GPT-4V for Multimodal Medical Diagnosis.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine Can GPT-4V(ision) Serve Medical Applications? Case Studies on GPT-4V for Multimodal Medical Diagnosis

Reference 59

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Source-reported events for the cited work

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Observation 360772cb-1472-4e1e-934d-18f1316792ab · outbound

This paper cites Towards Generalist Foundation Model for Radiology by Leveraging Web-scale 2D&3D Medical Data.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine Towards Generalist Foundation Model for Radiology by Leveraging Web-scale 2D&3D Medical Data

Reference 60

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Observation a26b6eee-0fca-48a4-a7db-b5e9c62f8bbf · outbound

This paper cites MediConfusion [ 49] probes failure modes on visually dissimilar image pairs.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine MediConfusion [ 49] probes failure modes on visually dissimilar image pairs

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:50:46.543033Z

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Observation ec15513e-c7ba-42c5-a280-4db773bee185 · outbound

This paper cites CARES: A Comprehensive Benchmark of Trustworthiness in Medical Vision Language Models.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine CARES: A Comprehensive Benchmark of Trustworthiness in Medical Vision Language Models

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-06T04:50:45.300767Z

Source-reported events for the cited work

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Observation 42125ddc-4570-45f7-b84c-5dba5e666f68 · outbound

This paper cites MedTrinity-25M: A Large-scale Multimodal Dataset with Multigranular Annotations for Medicine.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine MedTrinity-25M: A Large-scale Multimodal Dataset with Multigranular Annotations for Medicine

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-06T04:50:45.306820Z

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This paper cites Depth anything: Unleashing the power of large-scale unlabeled data.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine Depth anything: Unleashing the power of large-scale unlabeled data

Reference 64

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Observation d4185d3c-b5de-49c8-9e27-4923254fee06 · outbound

This paper cites Advancing Multimodal Medical Capabilities of Gemini.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine Advancing Multimodal Medical Capabilities of Gemini

Reference 65

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Observation 82cbc2ec-e34a-479a-ac03-8f78de3111f6 · outbound

This paper cites Gmai-mmbench: A comprehensive multimodal evaluation benchmark towards general medical ai.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine Gmai-mmbench: A comprehensive multimodal evaluation benchmark towards general medical ai

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:50:46.002495Z

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Observation d7768017-fca9-49a6-b8dd-6a6de030ffa8 · outbound

This paper cites PMC-VQA: Visual Instruction Tuning for Medical Visual Question Answering.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine PMC-VQA: Visual Instruction Tuning for Medical Visual Question Answering

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-06T04:50:45.328920Z

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Observation 8cfcdeb0-8fa5-4ce3-9f83-fe4581342e22 · outbound

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MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine Unresolved cited work

Reference 68

Resolution: parse uncertain; raw_fallback, observed 2026-08-06T04:50:45.983909Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 22370e71-3979-4e4d-8cf4-dbd23db8f2b5 · outbound

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MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine Unresolved cited work

Reference 69

Resolution: parse uncertain; raw_fallback, observed 2026-08-06T04:50:45.968069Z

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Observation 34fc5d89-f78b-4671-aa47-456e4ddfc969 · outbound

This paper cites an unresolved cited work.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine Unresolved cited work

Reference 70

Resolution: parse uncertain; raw_fallback, observed 2026-08-06T04:50:45.951271Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 04848663-0141-4fc7-b3ed-9f935c04c9e9 · outbound

This paper cites an unresolved cited work.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine Unresolved cited work

Reference 71

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Observation 710a4900-c0a2-41d9-bbfd-5c4fa6eb15e1 · outbound

This paper cites Here we use two versions as well, the 0.5B parameterized model, and 7B parameter- ized models.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine Here we use two versions as well, the 0.5B parameterized model, and 7B parameter- ized models

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:50:45.918541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b2e27d68-1e17-4fcc-bf01-fa012d90f9a5 · outbound

This paper cites Specifically, we prompt it with three questions and answers from PMC-VQA benchmark.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine Specifically, we prompt it with three questions and answers from PMC-VQA benchmark

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:50:45.900362Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation dbc38cef-16cb-40c4-93ca-4cd9ceffcb02 · outbound

This paper cites an unresolved cited work.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine Unresolved cited work

Reference 74

Resolution: unresolved; raw_fallback, observed 2026-08-06T04:50:45.882897Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Pith citing papers

Observation 47c153a4-45ee-4a12-91f4-2dc59ba0543a · inbound