Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare | Paper Citation Record

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare write newline

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare Shortcuts

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare K., Aggarwal, K., Som, S., Piao, S., and Wei, F

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare Multimodal datasets: misogyny, pornography, and malignant stereotypes

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare P., Kumar, A., Van Veen, D., Gardezi, S

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare C., Schwaighofer, A., Hyland, S., Wetscherek, M., Naumann, T., Nori, A., Alvarez-Valle, J., et al

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare On the Opportunities and Risks of Foundation Models

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare Multi-modal masked autoencoders for medical vision-and-language pre-training

Reference 8

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare W., Sutton, C., Gehrmann, S., et al

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare C., Hobbs, S

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare S., Reitsma, J

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare S., Moons, K

Reference 12

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare Embedding arithmetic of multimodal queries for image retrieval

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare RedCaps: web-curated image-text data created by the people, for the people

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare Coarse-to-fine vision-language pre-training with fusion in the backbone

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare Multi-modal alignment using representation codebook

Reference 16

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare Unresolved cited work

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare SimCSE: Simple Contrastive Learning of Sentence Embeddings

Reference 18

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare Uncurated image-text datasets: Shedding light on demographic bias

Reference 19

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare B., Visweswaran, S., and Batmanghelich, K

Reference 20

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare RadAlign: Advancing Radiology Report Generation with Vision-Language Concept Alignment

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare Vector quantized diffusion model for text-to-image synthesis

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare From Images to Textual Prompts: Zero-shot VQA with Frozen Large Language Models

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare Integrating medclip and cross-modal fusion for automatic radiology report generation

Reference 24

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare M., Griffith, B., and Klochko, C

Reference 25

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare D., Xu, D., and Popescu, M

Reference 26

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare Gans trained by a two time-scale update rule converge to a local nash equilibrium

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare P., and Yeung, S

Reference 29

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare Chexpert: A large chest radiograph dataset with uncertainty labels and expert comparison

Reference 30

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare Gpt-4 vision: Multi-modal evolution of chatgpt and potential role in radiology

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare Multimodal fusion with recurrent neural networks for rumor detection on microblogs

Reference 32

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare D., and Jawahar, C

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare H., Park, C

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare C., Lo, W.-Y., et al

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare Medclip-sam: Bridging text and image towards universal medical image segmentation

Reference 36

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare A., et al

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare VeCLIP: Improving CLIP Training via Visual-enriched Captions

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare Obelics: An open web-scale filtered dataset of interleaved image-text documents

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare Deep learning based approach for emotion recognition using image-text fusion

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare Pmc-clip: Contrastive language-image pre-training using biomedical documents

Reference 43

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare V., Ravazio, R., Kupssinsk \"u , L., Parraga, O., Delucis, M

Reference 44

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare Improving Zero-Shot Detection of Low Prevalence Chest Pathologies using Domain Pre-trained Language Models

Reference 45

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare RE-tune: Incremental Fine Tuning of Biomedical Vision-Language Models for Multi-label Chest X-ray Classification

Reference 46

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare H., Lee, H., Shin, W., Kim, Y.-H., and Choi, E

Reference 48

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs

Reference 49

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare P., Senadeera, M., Jacobs, S., Coghlan, S., and Le, V

Reference 51

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., et al

Reference 52

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This paper cites A., Tavakoli, N., Kim, G.

Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare A., Tavakoli, N., Kim, G

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:08:55.935577Z

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Observation 814f30d1-4384-403c-b858-3828154f2281 · outbound

This paper cites an unresolved cited work.

Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare Unresolved cited work

Reference 54

Resolution: unresolved; raw_fallback, observed 2026-08-15T22:08:55.888912Z

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Observation 2ea6c63f-ee01-41ef-890b-5ccaac743224 · outbound

This paper cites Zero-shot text-to-image generation.

Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare Zero-shot text-to-image generation

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-15T22:08:54.214968Z

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare SAM.MD: Zero-shot medical image segmentation capabilities of the Segment Anything Model

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-15T22:08:54.217871Z

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This paper cites Improved techniques for training gans.

Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare Improved techniques for training gans

Reference 57

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This paper cites Conceptual captions: A cleaned, hypernymed, image alt-text dataset for automatic image captioning.

Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare Conceptual captions: A cleaned, hypernymed, image alt-text dataset for automatic image captioning

Reference 58

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This paper cites Flava: A foundational language and vision alignment model.

Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare Flava: A foundational language and vision alignment model

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:08:55.835733Z

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Observation ceb1a20e-3987-427b-bbba-9974dd450b3c · outbound

This paper cites A., Newsome, J.

Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare A., Newsome, J

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:08:55.792379Z

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Observation 10e877c9-f15c-40d9-8f62-829d7085f3e9 · outbound

This paper cites S., Klontzas, M.

Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare S., Klontzas, M

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:08:55.777977Z

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Observation be92c6c6-23f6-47bb-8450-3c00dac42ef4 · outbound

This paper cites S., Klontzas, M.

Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare S., Klontzas, M

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:08:55.729836Z

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Observation 4e76d904-a44d-4e31-bdba-5d29f1614f85 · outbound

This paper cites P., Ng, A.

Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare P., Ng, A

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:08:55.678548Z

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Observation aa316863-4973-4ab1-a82c-770a5e40909a · outbound

This paper cites On large visual language models for medical imaging analysis: An empirical study.

Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare On large visual language models for medical imaging analysis: An empirical study

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:08:55.665278Z

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Observation 6837b7c7-cf75-4511-b8a7-42a60dc8c0d4 · outbound

This paper cites Q., Wang, L., Wong, K.

Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare Q., Wang, L., Wong, K

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:08:55.552879Z

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Observation 371e875d-df8b-4235-b45b-c9f19f0b16ee · outbound

This paper cites Med-unic: Unifying cross-lingual medical vision-language pre-training by diminishing bias.

Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare Med-unic: Unifying cross-lingual medical vision-language pre-training by diminishing bias

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:08:55.542299Z

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Observation 4b8fa883-4344-445c-8217-ab2f41805d3a · outbound

This paper cites L., and Boker, H.

Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare L., and Boker, H

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:08:55.484610Z

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Observation eeb9eb76-9ba0-445c-9183-14dc4453fe94 · outbound

This paper cites MedCLIP: Contrastive Learning from Unpaired Medical Images and Text.

Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare MedCLIP: Contrastive Learning from Unpaired Medical Images and Text

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-15T22:08:54.410577Z

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Observation 6abd2a33-8bd8-4b9c-9af6-517baafa63d7 · outbound

This paper cites Medim: Boost medical image representation via radiology report-guided masking.

Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare Medim: Boost medical image representation via radiology report-guided masking

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:08:55.329823Z

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Observation 43426e7b-abff-4d55-821e-d9b778167300 · outbound

This paper cites VideoCLIP: Contrastive Pre-training for Zero-shot Video-Text Understanding.

Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare VideoCLIP: Contrastive Pre-training for Zero-shot Video-Text Understanding

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-15T22:08:54.433543Z

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Unavailable: canonical work link unavailable.

Observation 39ea49d6-e75e-4fbd-9f6d-7994dccd8037 · outbound

This paper cites Versatile diffusion: Text, images and variations all in one diffusion model.

Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare Versatile diffusion: Text, images and variations all in one diffusion model

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-15T22:08:54.476749Z

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Unavailable: canonical work link unavailable.

Observation eb279fc9-6f07-461c-94a6-6c5aa026dbe1 · outbound

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Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare T., Bajwa, J., Jacob, J., Pinnock, M

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:08:55.312159Z

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Observation 53ab1b95-b7b8-4ea9-8c21-d36fefe4232c · outbound

This paper cites K., Baek, W., and Roh, B.

Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare K., Baek, W., and Roh, B

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:08:55.231367Z

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Observation 7d271b10-f897-404a-a69f-38702a0512f0 · outbound

This paper cites Attention prompting on image for large vision-language models.

Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare Attention prompting on image for large vision-language models

Reference 74

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Observation 0d86fa0a-8a6e-4738-a79e-4d66feaec5f6 · outbound

This paper cites and Ma \'n dziuk, J.

Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare and Ma \'n dziuk, J

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:08:55.138800Z

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Observation 942123b7-13ab-4540-9a26-0bcaafca0ab8 · outbound

This paper cites Multi-task paired masking with alignment modeling for medical vision-language pre-training.

Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare Multi-task paired masking with alignment modeling for medical vision-language pre-training

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:08:55.076390Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8d50aab7-018a-4165-b415-52e0f980fdd9 · outbound

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

Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare BiomedCLIP: a multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairs

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-15T22:08:54.560375Z

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Observation db5c1396-bfb9-4d88-accc-bb0915e3eb3e · outbound

This paper cites D., and Langlotz, C.

Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare D., and Langlotz, C

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:08:55.043329Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7f9f042d-e487-40e5-b7cd-65cc0cb03ed6 · outbound

This paper cites A multimodal fusion approach for image captioning.

Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare A multimodal fusion approach for image captioning

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:08:55.010492Z

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Observation 41f78e6f-b1a0-480d-a617-59a256885388 · outbound

This paper cites Fine-tuning Large Language Models for Domain-specific Machine Translation.

Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare Fine-tuning Large Language Models for Domain-specific Machine Translation

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-15T22:08:54.623101Z

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Unavailable: canonical work link unavailable.

Observation c2cbf813-de19-4b06-ae4b-53a00f9d45b9 · outbound

This paper cites Advancing Radiograph Representation Learning with Masked Record Modeling.

Position: Restructuring of Categories and Implementation of Guidelines Essential for VLM Adoption in Healthcare Advancing Radiograph Representation Learning with Masked Record Modeling

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-15T22:08:54.627585Z

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Unavailable: canonical work link unavailable.

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Outbound references

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