Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis | Paper Citation Record

Observation 5d0d3653-3d7a-4df1-a342-89d5e19f6b26 · outbound

This paper cites Edge-competing pathological liver vessel segmentation with limited labels,.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis Edge-competing pathological liver vessel segmentation with limited labels,

Reference 1

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Observation 38951201-3471-4cd5-925f-e0a119f9997b · outbound

This paper cites Mutual-complementing framework for nuclei detection and segmentation in pathology image,.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis Mutual-complementing framework for nuclei detection and segmentation in pathology image,

Reference 2

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Observation 278b9c2c-9d05-4541-92cf-df2d3218df4a · outbound

This paper cites A loopback network for explainable microvascular invasion classification,.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis A loopback network for explainable microvascular invasion classification,

Reference 3

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Observation c3f77198-6166-4652-927c-b3a07988d4b8 · outbound

This paper cites Scaling vision transformers to gigapixel images via hierar- chical self-supervised learning,.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis Scaling vision transformers to gigapixel images via hierar- chical self-supervised learning,

Reference 4

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Observation 75000f35-bd74-487a-a739-7c500f02af75 · outbound

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

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis Towards a general-purpose foundation model for computational pathology,

Reference 5

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Observation bf14420d-b194-4a0e-96d6-24de6253523a · outbound

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

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis A whole-slide foundation model for digital pathology from real-world data,

Reference 6

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Observation ede887e8-3d1e-484e-962a-26b7405c363a · outbound

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

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis A foundation model for clinical-grade computa- tional pathology and rare cancers detection,

Reference 7

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Observation 94497e93-af58-4739-a1e3-73543347147a · outbound

This paper cites A pathology foundation model for cancer diagnosis and prognosis prediction,.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis A pathology foundation model for cancer diagnosis and prognosis prediction,

Reference 8

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Observation 56a02a1b-54e5-46d7-9622-2c2884de5865 · outbound

This paper cites GPT-4 Technical Report.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis GPT-4 Technical Report

Reference 9

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Observation dd32b1e1-e59e-489c-91d5-eb40e6a7960c · outbound

This paper cites The Llama 3 Herd of Models.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis The Llama 3 Herd of Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-11T17:02:22.299191Z

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Observation 0c0907d0-23d5-48d3-b78b-4c0dce9ccdeb · outbound

This paper cites Qwen2.5 Technical Report.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis Qwen2.5 Technical Report

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-11T17:02:22.309605Z

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Observation 95541a36-5f7f-4507-b053-0bc7b9b2e037 · outbound

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

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 12

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Observation 510081e1-9b1e-45df-a423-50bf716fb48e · outbound

This paper cites Improved baselines with visual instruction tuning,.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis Improved baselines with visual instruction tuning,

Reference 13

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Observation c2d96673-c5d4-4469-ac6b-e03afedbbe50 · outbound

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

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 14

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Observation 45b918e3-e93d-46f7-a3c7-5120618dd5bb · outbound

This paper cites Shikra: Unleashing Multimodal LLM's Referential Dialogue Magic.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis Shikra: Unleashing Multimodal LLM's Referential Dialogue Magic

Reference 15

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Observation b80e359b-759d-44b8-8687-24346fa11ee6 · outbound

This paper cites Lisa: Reasoning segmentation via large language model,.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis Lisa: Reasoning segmentation via large language model,

Reference 16

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Observation e89ca2cf-81ad-45ba-8eb4-7647b41653f5 · outbound

This paper cites Pathmmu: A massive multimodal expert-level benchmark for understanding and reasoning in pathology,.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis Pathmmu: A massive multimodal expert-level benchmark for understanding and reasoning in pathology,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:02:24.494615Z

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Observation f4edeaff-70ef-41dd-afd3-1869951272c6 · outbound

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

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis A multimodal generative ai copilot for human pathology,

Reference 20

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Observation 113a1878-3d93-414b-9b2c-0b2333d7d273 · outbound

This paper cites PathAlign: A vision-language model for whole slide images in histopathology.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis PathAlign: A vision-language model for whole slide images in histopathology

Reference 21

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Observation fab01df4-a7c4-4938-a156-cbd0cddb77c8 · outbound

This paper cites PA-LLaVA: A Large Language-Vision Assistant for Human Pathology Image Understanding.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis PA-LLaVA: A Large Language-Vision Assistant for Human Pathology Image Understanding

Reference 22

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Observation 1b8f6c1f-a85e-4052-8aa6-8d859c3bc1e7 · outbound

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

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis PathGen-1.6M: 1.6 Million Pathology Image-text Pairs Generation through Multi-agent Collaboration

Reference 23

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Observation 8927fd73-c638-4be0-9a5e-fb91fcdc28ca · outbound

This paper cites PRISM: A Multi-Modal Generative Foundation Model for Slide-Level Histopathology.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis PRISM: A Multi-Modal Generative Foundation Model for Slide-Level Histopathology

Reference 24

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Observation fc2bc8f2-8b12-4257-8897-8ad6e6f162b6 · outbound

This paper cites Multiple instance captioning: Learning representations from histopathology textbooks and articles,.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis Multiple instance captioning: Learning representations from histopathology textbooks and articles,

Reference 25

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Observation a2001eed-28bc-4625-8830-3a5c0b4e03fe · outbound

This paper cites Wsi-vqa: Interpreting whole slide images by generative visual question answering,.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis Wsi-vqa: Interpreting whole slide images by generative visual question answering,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:02:24.380253Z

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Observation 972a90bc-ddfe-4f65-b2d5-c620a3064200 · outbound

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

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis A visual–language foun- dation model for pathology image analysis using medical twitter,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:02:24.347378Z

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Observation 3729abe6-f3fc-4874-af46-2fbe61fa427c · outbound

This paper cites Quilt-1m: One million image-text pairs for histopathology,.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis Quilt-1m: One million image-text pairs for histopathology,

Reference 29

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Observation 1d005a73-7197-4320-9c18-aaefac81fb44 · outbound

This paper cites Attention-based deep multiple instance learning,.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis Attention-based deep multiple instance learning,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:02:24.304326Z

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Observation d339acec-81ba-40f5-a9f4-326eed152019 · outbound

This paper cites Transmil: Transformer based correlated multiple instance learning for whole slide image classification,.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis Transmil: Transformer based correlated multiple instance learning for whole slide image classification,

Reference 31

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Observation 14327c20-ee6c-45d8-a375-e5a5a19b4da3 · outbound

This paper cites Camel: A weakly supervised learning framework for histopathol- ogy image segmentation,.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis Camel: A weakly supervised learning framework for histopathol- ogy image segmentation,

Reference 32

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Observation 0bac08d6-83d9-4066-bf62-f25a5addc6aa · outbound

This paper cites Differentiable zooming for multiple instance learning on whole-slide images,.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis Differentiable zooming for multiple instance learning on whole-slide images,

Reference 33

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This paper cites PathInsight: Instruction Tuning of Multimodal Datasets and Models for Intelligence Assisted Diagnosis in Histopathology.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis PathInsight: Instruction Tuning of Multimodal Datasets and Models for Intelligence Assisted Diagnosis in Histopathology

Reference 34

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This paper cites Visual instruction tuning,.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis Visual instruction tuning,

Reference 35

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Observation 96defe81-3412-4d52-bdf2-e16c3e0eb53f · outbound

This paper cites Learning transferable visual models from natu- ral language supervision,.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis Learning transferable visual models from natu- ral language supervision,

Reference 36

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Observation 9b569e5a-295f-49d0-a79a-82e2d42e4068 · outbound

This paper cites Training language models to follow instructions with human feedback,.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis Training language models to follow instructions with human feedback,

Reference 37

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Observation 47d74f6e-3736-43df-a0cc-db7de960a17f · outbound

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

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models,

Reference 38

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Observation d5b83687-3f3f-4a0b-9569-a31f4ee07a21 · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis DINOv2: Learning Robust Visual Features without Supervision

Reference 40

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This paper cites Sigmoid loss for language image pre- training,.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis Sigmoid loss for language image pre- training,

Reference 41

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Observation 6fbf1ecf-92e1-456b-a472-a6209d3bb2e0 · outbound

This paper cites Deep residual learning for image recognition,.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis Deep residual learning for image recognition,

Reference 42

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Observation 703ded8a-c120-45a0-8fd6-bc71ce895d07 · outbound

This paper cites Segment anything,.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis Segment anything,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:02:24.008849Z

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Observation 540a0554-2ca7-458a-ad88-f0e939d45fed · outbound

This paper cites Integrative analysis of histological textures and lymphocyte infiltration in renal cell carcinoma using deep learning,.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis Integrative analysis of histological textures and lymphocyte infiltration in renal cell carcinoma using deep learning,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:02:23.980041Z

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Observation be340a1f-47d3-4dcc-9de2-f3144be33b7b · outbound

This paper cites A petri dish for histopathology image analysis,.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis A petri dish for histopathology image analysis,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:02:23.938594Z

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Observation 336d9364-0b1d-4fa6-841e-e40a6fafc691 · outbound

This paper cites A method for normalizing histology slides for quantitative analysis,.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis A method for normalizing histology slides for quantitative analysis,

Reference 46

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Observation ad27ab90-d956-4304-a060-22fba89ead89 · outbound

This paper cites Artificial intelligence for diagnosis and gleason grading of prostate cancer: The panda challenge,.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis Artificial intelligence for diagnosis and gleason grading of prostate cancer: The panda challenge,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:02:23.904222Z

Source-reported events for the cited work

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Observation aca5d412-4a06-4476-92c4-dedd6272467a · outbound

This paper cites Pathologist- level classification of histologic patterns on resected lung adenocarcinoma slides with deep neural networks,.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis Pathologist- level classification of histologic patterns on resected lung adenocarcinoma slides with deep neural networks,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:02:23.865061Z

Source-reported events for the cited work

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Observation ffeb5248-e6e2-45ae-a18f-162ab81841fc · outbound

This paper cites 1399 h&e-stained sentinel lymph node sections of breast cancer patients: The camelyon dataset,.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis 1399 h&e-stained sentinel lymph node sections of breast cancer patients: The camelyon dataset,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:02:23.829796Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation bc55f360-03bc-4210-b685-ba538a651e7a · outbound

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

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis Llava-med: Training a large language-and-vision assistant for biomedicine in one day,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:02:24.111020Z

Source-reported events for the cited work

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Observation 7de88dfc-abaf-4a95-ac84-4ae1e95bf2bc · outbound

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

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis Quilt-llava: Visual instruction tuning by extracting localized narratives from open-source histopathology videos,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:02:24.463967Z

Source-reported events for the cited work

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Observation d29c2615-92d9-4f2c-bac7-a1747951cc67 · outbound

This paper cites Jocher and J.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis Jocher and J

Reference 55

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Source-reported events for the cited work

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Observation ce0750ff-05ce-49f5-811e-a6d5f1fe07cb · outbound

This paper cites Nnu-net: A self- configuring method for deep learning-based biomedical image segmentation,.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis Nnu-net: A self- configuring method for deep learning-based biomedical image segmentation,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:02:23.722237Z

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Observation 9ba6823c-f4e5-4fc2-9583-5f190e4396b3 · outbound

This paper cites A multi-organ nucleus segmentation challenge,.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis A multi-organ nucleus segmentation challenge,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:02:23.805647Z

Source-reported events for the cited work

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Observation f29d7be6-b4a8-4032-96c5-e74e30367b7d · outbound

This paper cites Conic challenge: Pushing the frontiers of nu- clear detection, segmentation, classification and counting,.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis Conic challenge: Pushing the frontiers of nu- clear detection, segmentation, classification and counting,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:02:23.695571Z

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Observation 76938bee-cd3b-42cf-9ca2-22734818130b · outbound

This paper cites an unresolved cited work.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis Unresolved cited work

Reference 59

Resolution: verified exact; doi, observed 2026-08-11T17:02:22.979327Z

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This paper cites Nucls: A scalable crowdsourcing approach and dataset for nucleus classification and segmentation in breast cancer,.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis Nucls: A scalable crowdsourcing approach and dataset for nucleus classification and segmentation in breast cancer,

Reference 60

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This paper cites PanNuke Dataset Extension, Insights and Baselines.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis PanNuke Dataset Extension, Insights and Baselines

Reference 61

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This paper cites Nuinsseg: A fully annotated dataset for nuclei instance segmentation in h&e-stained histological images,.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis Nuinsseg: A fully annotated dataset for nuclei instance segmentation in h&e-stained histological images,

Reference 62

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This paper cites Artificial intelligence for tumour tissue detection and histological regression grading in oesophageal adenocarcinomas: A retrospective algorithm development and validation study,.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis Artificial intelligence for tumour tissue detection and histological regression grading in oesophageal adenocarcinomas: A retrospective algorithm development and validation study,

Reference 63

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This paper cites Deep learning-based mapping of tumor infiltrating lymphocytes in whole slide images of 23 types of cancer,.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis Deep learning-based mapping of tumor infiltrating lymphocytes in whole slide images of 23 types of cancer,

Reference 64

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Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis Unresolved cited work

Reference 65

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This paper cites Universal encoding of pan-cancer histology by deep texture representations,.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis Universal encoding of pan-cancer histology by deep texture representations,

Reference 66

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

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis Pathasst: A generative foundation ai assistant towards artificial general intelligence of pathology,

Reference 67

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This paper cites PathVQA: 30000+ Questions for Medical Visual Question Answering.

Efficient and Comprehensive Feature Extraction in Large Vision-Language Model for Pathology Analysis PathVQA: 30000+ Questions for Medical Visual Question Answering

Reference 68

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