DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis | Paper Citation Record

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This paper cites Computational pathology: A comprehensive review of recent developments in digital and intelligent pathology,.

DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis Computational pathology: A comprehensive review of recent developments in digital and intelligent pathology,

Reference 1

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Observation e7f971f3-a4f4-4b36-be0e-8819527d5e2f · outbound

This paper cites A whole-slide foundation model for digital pathology from real-world data,.

DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis A whole-slide foundation model for digital pathology from real-world data,

Reference 2

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Observation b2d04947-9c2c-4b6e-8c37-b9234b433398 · outbound

This paper cites Burden and cost of gastrointestinal, liver, and pancreatic diseases in the united states: Update 2024,.

DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis Burden and cost of gastrointestinal, liver, and pancreatic diseases in the united states: Update 2024,

Reference 3

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This paper cites Patterns of upper gas- trointestinal diseases among patients undergoing esophagogastroduo- denoscopy at three hospitals in asella town, southeast ethiopia,.

DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis Patterns of upper gas- trointestinal diseases among patients undergoing esophagogastroduo- denoscopy at three hospitals in asella town, southeast ethiopia,

Reference 4

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This paper cites Quality indicators for upper gi endoscopy,.

DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis Quality indicators for upper gi endoscopy,

Reference 5

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Observation 6b78f758-bdbc-48e8-a7e2-2aa94fe63a7e · outbound

This paper cites The current troubled state of the global pathology workforce: a concise review,.

DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis The current troubled state of the global pathology workforce: a concise review,

Reference 6

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This paper cites Enhancing whole slide image classification with discriminative and contrastive learning,.

DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis Enhancing whole slide image classification with discriminative and contrastive learning,

Reference 7

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Observation 7e408306-a8ee-4c00-8627-1e98897fe758 · outbound

This paper cites Application of deep learning convolutional neural networks to identify gastric squamous cell carcinoma in mice,.

DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis Application of deep learning convolutional neural networks to identify gastric squamous cell carcinoma in mice,

Reference 8

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This paper cites Qwen2.5-VL Technical Report.

DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis Qwen2.5-VL Technical Report

Reference 9

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This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 10

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This paper cites Medpath: Augmenting health risk prediction via medical knowledge paths,.

DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis Medpath: Augmenting health risk prediction via medical knowledge paths,

Reference 11

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This paper cites Generating dermatopathology reports from gigapixel whole slide im- ages with histogpt,.

DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis Generating dermatopathology reports from gigapixel whole slide im- ages with histogpt,

Reference 12

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This paper cites Computational pathology, new horizons and challenges for anatomical pathology,.

DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis Computational pathology, new horizons and challenges for anatomical pathology,

Reference 13

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This paper cites Closing the loop–the role of pathologists in digital and computational pathology research,.

DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis Closing the loop–the role of pathologists in digital and computational pathology research,

Reference 14

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This paper cites Synoptic reporting by summarizing cancer pathology reports using large language models,.

DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis Synoptic reporting by summarizing cancer pathology reports using large language models,

Reference 15

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This paper cites A framework to assess clinical safety and hallucination rates of llms for medical text summarisation,.

DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis A framework to assess clinical safety and hallucination rates of llms for medical text summarisation,

Reference 16

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This paper cites Benchmark pathology report text corpus with cancer type classification,.

DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis Benchmark pathology report text corpus with cancer type classification,

Reference 17

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This paper cites Impact of template-based synoptic reporting on completeness of surgical pathology reports,.

DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis Impact of template-based synoptic reporting on completeness of surgical pathology reports,

Reference 18

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Observation 46e5e808-d79e-4eb1-b1fe-5d87d1bac387 · outbound

This paper cites The 1 million words pathology report or the challenge of a reproducible and meaningful message,.

DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis The 1 million words pathology report or the challenge of a reproducible and meaningful message,

Reference 19

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This paper cites Multimodal Whole Slide Foundation Model for Pathology.

DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis Multimodal Whole Slide Foundation Model for Pathology

Reference 20

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This paper cites A foundation model for clinical-grade computational pathology and rare cancers detection,.

DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis A foundation model for clinical-grade computational pathology and rare cancers detection,

Reference 21

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This paper cites Towards a general-purpose foundation model for computational pathology,.

DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis Towards a general-purpose foundation model for computational pathology,

Reference 22

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This paper cites Transformer-based unsupervised contrastive learning for histopathological image classification,.

DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis Transformer-based unsupervised contrastive learning for histopathological image classification,

Reference 23

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This paper cites A visual-language foundation model for computational pathology,.

DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis A visual-language foundation model for computational pathology,

Reference 24

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This paper cites A visual–language foundation model for pathology image analysis using medical twitter,.

DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis A visual–language foundation model for pathology image analysis using medical twitter,

Reference 25

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

DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis Learning transferable visual models from natural language supervision,

Reference 26

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DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis Visual instruction tuning,

Reference 27

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This paper cites Improved baselines with visual instruction tuning,.

DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis Improved baselines with visual instruction tuning,

Reference 28

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This paper cites Pathasst: A generative foundation ai assistant towards artificial general intelligence of pathology,.

DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis Pathasst: A generative foundation ai assistant towards artificial general intelligence of pathology,

Reference 29

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This paper cites Towards A Generalizable Pathology Foundation Model via Unified Knowledge Distillation.

DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis Towards A Generalizable Pathology Foundation Model via Unified Knowledge Distillation

Reference 30

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This paper cites A Multimodal Knowledge-enhanced Whole-slide Pathology Foundation Model.

DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis A Multimodal Knowledge-enhanced Whole-slide Pathology Foundation Model

Reference 31

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This paper cites Biogpt: generative pre-trained transformer for biomedical text genera- tion and mining,.

DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis Biogpt: generative pre-trained transformer for biomedical text genera- tion and mining,

Reference 32

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This paper cites A multimodal generative ai copilot for human pathology,.

DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis A multimodal generative ai copilot for human pathology,

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This paper cites 4v (ision) system card https://cdn. openai. com/papers,.

DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis 4v (ision) system card https://cdn. openai. com/papers,

Reference 34

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

DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis Quilt-llava: Visual instruction tuning by extracting localized narratives from open-source histopathology videos,

Reference 35

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This paper cites Histgen: Histopathology report generation via local-global feature encoding and cross-modal context interaction,.

DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis Histgen: Histopathology report generation via local-global feature encoding and cross-modal context interaction,

Reference 36

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This paper cites VLM-R1: A Stable and Generalizable R1-style Large Vision-Language Model.

DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis VLM-R1: A Stable and Generalizable R1-style Large Vision-Language Model

Reference 37

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DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models

Reference 38

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DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis OpenAI o1 System Card

Reference 39

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This paper cites LlamaV-o1: Rethinking Step-by-step Visual Reasoning in LLMs.

DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis LlamaV-o1: Rethinking Step-by-step Visual Reasoning in LLMs

Reference 40

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DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis Visual-RFT: Visual Reinforcement Fine-Tuning

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This paper cites HistoGym: A Reinforcement Learning Environment for Histopathological Image Analysis.

DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis HistoGym: A Reinforcement Learning Environment for Histopathological Image Analysis

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This paper cites Dual attention model with reinforcement learning for classification of histology whole-slide images,.

DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis Dual attention model with reinforcement learning for classification of histology whole-slide images,

Reference 43

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This paper cites Med-r1: Reinforcement learning for generalizable medical reasoning in vision-language models,.

DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis Med-r1: Reinforcement learning for generalizable medical reasoning in vision-language models,

Reference 44

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This paper cites Proximal Policy Optimization Algorithms.

DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis Proximal Policy Optimization Algorithms

Reference 45

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This paper cites PathGen-1.6M: 1.6 Million Pathology Image-text Pairs Generation through Multi-agent Collaboration.

DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis PathGen-1.6M: 1.6 Million Pathology Image-text Pairs Generation through Multi-agent Collaboration

Reference 46

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