PathView-Bench: Can Multimodal Large Language Models Achieve Fine-grained Multiscale Understanding of Pathology Images? | Paper Citation Record

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PathView-Bench: Can Multimodal Large Language Models Achieve Fine-grained Multiscale Understanding of Pathology Images? Image analysis and machine learning in digital pathology: Challenges and opportunities.Medical image analysis, 33:170–175, 2016

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This paper cites Digital pathology and artificial intelligence.The lancet oncology, 20(5):e253–e261, 2019.

PathView-Bench: Can Multimodal Large Language Models Achieve Fine-grained Multiscale Understanding of Pathology Images? Digital pathology and artificial intelligence.The lancet oncology, 20(5):e253–e261, 2019

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PathView-Bench: Can Multimodal Large Language Models Achieve Fine-grained Multiscale Understanding of Pathology Images? Clinical-grade computational pathology using weakly supervised deep learning on whole slide images.Nature medicine, 25(8):1301–1309, 2019

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PathView-Bench: Can Multimodal Large Language Models Achieve Fine-grained Multiscale Understanding of Pathology Images? Data-efficient and weakly supervised computational pathology on whole-slide images.Nature biomedical engineering, 5(6):555–570, 2021

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PathView-Bench: Can Multimodal Large Language Models Achieve Fine-grained Multiscale Understanding of Pathology Images? Feature re-embedding: Towards foundation model-level performance in computational pathology

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PathView-Bench: Can Multimodal Large Language Models Achieve Fine-grained Multiscale Understanding of Pathology Images? M4: Multi-proxy multi-gate mixture of experts network for multiple instance learning in histopathology image analysis.Medical Image Analysis, 103:103561, 2025

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PathView-Bench: Can Multimodal Large Language Models Achieve Fine-grained Multiscale Understanding of Pathology Images? Smmile enables accurate spatial quantification in digital pathology using multiple-instance learning.Nature Cancer, pages 1–17, 2025

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PathView-Bench: Can Multimodal Large Language Models Achieve Fine-grained Multiscale Understanding of Pathology Images? A pathology foundation model for cancer diagnosis and prognosis prediction.Nature, 634(8035):970–978, 2024

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PathView-Bench: Can Multimodal Large Language Models Achieve Fine-grained Multiscale Understanding of Pathology Images? A vision–language foundation model for precision oncology.Nature, 638(8051):769–778, 2025

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PathView-Bench: Can Multimodal Large Language Models Achieve Fine-grained Multiscale Understanding of Pathology Images? A generalizable pathology foundation model using a unified knowledge distillation pretraining framework.Nature Biomedical Engineering, pages 1–20, 2025

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PathView-Bench: Can Multimodal Large Language Models Achieve Fine-grained Multiscale Understanding of Pathology Images? Pathasst: A generative foundation ai assistant towards artificial general intelligence of pathology

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PathView-Bench: Can Multimodal Large Language Models Achieve Fine-grained Multiscale Understanding of Pathology Images? Quilt-llava: Visual instruction tuning by extracting localized narratives from open-source histopathology videos

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PathView-Bench: Can Multimodal Large Language Models Achieve Fine-grained Multiscale Understanding of Pathology Images? Cpath-omni: A unified multimodal foundation model for patch and whole slide image analysis in computational pathology

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PathView-Bench: Can Multimodal Large Language Models Achieve Fine-grained Multiscale Understanding of Pathology Images? Patho-agenticrag: towards multimodal agentic retrieval-augmented generation for pathology vlms via reinforcement learning

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PathView-Bench: Can Multimodal Large Language Models Achieve Fine-grained Multiscale Understanding of Pathology Images? Wsicaption: Multiple instance generation of pathology reports for gigapixel whole-slide images

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PathView-Bench: Can Multimodal Large Language Models Achieve Fine-grained Multiscale Understanding of Pathology Images? Histgen: Histopathol- ogy report generation via local-global feature encoding and cross-modal context interaction

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PathView-Bench: Can Multimodal Large Language Models Achieve Fine-grained Multiscale Understanding of Pathology Images? Generating der- matopathology reports from gigapixel whole slide images with histogpt.Nature communications, 16(1): 4886, 2025

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Observation d89db2b3-e227-4a50-bd36-fe48366a8526 · outbound

This paper cites GLM-4.5V and GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning.

PathView-Bench: Can Multimodal Large Language Models Achieve Fine-grained Multiscale Understanding of Pathology Images? GLM-4.5V and GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning

Reference 50

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Observation 9eac6142-4919-48ec-83d6-77f5d935a294 · outbound

This paper cites MedGemma Technical Report.

PathView-Bench: Can Multimodal Large Language Models Achieve Fine-grained Multiscale Understanding of Pathology Images? MedGemma Technical Report

Reference 51

Resolution: unresolved; no resolver link, observed 2026-07-31T11:25:33.314380Z

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Observation df2cc097-0eca-4162-8d90-b8dad3c02646 · outbound

This paper cites MedGemma 1.5 Technical Report.

PathView-Bench: Can Multimodal Large Language Models Achieve Fine-grained Multiscale Understanding of Pathology Images? MedGemma 1.5 Technical Report

Reference 52

Resolution: unresolved; no resolver link, observed 2026-07-31T11:25:33.316821Z

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Observation c6f8719f-9d93-4c49-8dd5-6f54af641860 · outbound

This paper cites Swift: a scalable lightweight infrastructure for fine-tuning.

PathView-Bench: Can Multimodal Large Language Models Achieve Fine-grained Multiscale Understanding of Pathology Images? Swift: a scalable lightweight infrastructure for fine-tuning

Reference 53

Resolution: unresolved; no resolver link, observed 2026-07-31T11:25:33.319256Z

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