Paper Citation Record · LEDGER

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification

As of 20 August 2026, this Paper Citation Record lists 60 of 60 outbound references and 1 inbound Pith citation observation for arXiv:2411.14743.

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

pith.paper-citation-record.v1
2411.14743 v2

Coverage vector

measured 60 of 60 reference resolution

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measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Reference resolution

60 of 60 outbound references displayed

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External citation measurements

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Outbound references

Observation 9df220b4-ab1a-4c8a-991c-7ad713920a27 · outbound

This paper cites GPT-4 Technical Report.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification GPT-4 Technical Report

Reference 1

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Observation 780fd463-2d7e-401c-90cc-71a6d1702f34 · outbound

This paper cites Computing re- ceptive fields of convolutional neural networks.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification Computing re- ceptive fields of convolutional neural networks

Reference 2

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Observation 7bb1e2d7-4cf9-4962-a6b2-6620c1c79565 · outbound

This paper cites From detection of individual metastases to classification of lymph node status at the pa- tient level: the camelyon17 challenge.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification From detection of individual metastases to classification of lymph node status at the pa- tient level: the camelyon17 challenge

Reference 3

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This paper cites Diagnos- tic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification Diagnos- tic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer

Reference 4

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Observation 91cc0383-5144-45a7-a242-39176a281e41 · outbound

This paper cites Clinical-grade computational pathology using weakly supervised deep learning on whole slide images.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification Clinical-grade computational pathology using weakly supervised deep learning on whole slide images

Reference 5

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Observation 3bd62031-1d14-4855-87ea-82bace6286b4 · outbound

This paper cites Pathomic fusion: an integrated framework for fusing histopathology and genomic features for cancer diag- nosis and prognosis.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification Pathomic fusion: an integrated framework for fusing histopathology and genomic features for cancer diag- nosis and prognosis

Reference 6

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Observation 5f46fa2e-eac7-40b8-959d-51d8d32a7bd8 · outbound

This paper cites Pan-cancer in- tegrative histology-genomic analysis via multimodal deep learning.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification Pan-cancer in- tegrative histology-genomic analysis via multimodal deep learning

Reference 7

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Observation ff69381f-5af2-4df5-8b96-b6f1748cef76 · outbound

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

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification Towards a general-purpose foundation model for computational pathology

Reference 8

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This paper cites Multiple instance learn- ing with center embeddings for histopathology classifica- tion.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification Multiple instance learn- ing with center embeddings for histopathology classifica- tion

Reference 9

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Observation 265351a4-8608-4b5b-9528-4322c2b4761b · outbound

This paper cites Artificial intelligence and computational pathology.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification Artificial intelligence and computational pathology

Reference 10

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Observation 0e963c6b-9eb4-48e3-b60e-5da2a4f95554 · outbound

This paper cites Beyond h&e: Unlocking pathological insights with polarization via self- supervised learning.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification Beyond h&e: Unlocking pathological insights with polarization via self- supervised learning

Reference 11

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Observation 3314cbad-5362-46b7-a6d3-d8b04d941c22 · outbound

This paper cites The Llama 3 Herd of Models.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification The Llama 3 Herd of Models

Reference 12

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Observation e7a45ac8-4a49-4253-ac6d-d61033c85505 · outbound

This paper cites FAST: A Dual-tier Few-Shot Learning Paradigm for Whole Slide Image Classification.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification FAST: A Dual-tier Few-Shot Learning Paradigm for Whole Slide Image Classification

Reference 13

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Observation dbc6326b-68a9-40a6-b6e7-bc506960d93d · outbound

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

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification Histgen: Histopathology re- port generation via local-global feature encoding and cross- modal context interaction

Reference 14

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Observation 99921291-dec2-42f9-aa43-dee517b9fdd1 · outbound

This paper cites Context Matters: Query-aware Dynamic Long Sequence Modeling of Gigapixel Images.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification Context Matters: Query-aware Dynamic Long Sequence Modeling of Gigapixel Images

Reference 15

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Observation 4e669472-f162-4385-a54c-0212c4bc9d17 · outbound

This paper cites MSCPT: Few-shot Whole Slide Image Classification with Multi-scale and Context-focused Prompt Tuning.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification MSCPT: Few-shot Whole Slide Image Classification with Multi-scale and Context-focused Prompt Tuning

Reference 16

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This paper cites Computational pathology: a survey review and the way forward.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification Computational pathology: a survey review and the way forward

Reference 17

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Observation 1f82a76c-5c76-4ade-aa16-c5718a880894 · outbound

This paper cites Hˆ 2-mil: ex- ploring hierarchical representation with heterogeneous mul- tiple instance learning for whole slide image analysis.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification Hˆ 2-mil: ex- ploring hierarchical representation with heterogeneous mul- tiple instance learning for whole slide image analysis

Reference 18

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Observation 4e447e6b-458f-490a-8798-784010f50c00 · outbound

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

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification A visual–language foundation model for pathology image analysis using medical twitter

Reference 19

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This paper cites Attention-based deep multiple instance learning.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification Attention-based deep multiple instance learning

Reference 20

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Observation 9660dbe0-9db1-423b-90c5-f8108bee553a · outbound

This paper cites Model- ing dense multimodal interactions between biological path- ways and histology for survival prediction.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification Model- ing dense multimodal interactions between biological path- ways and histology for survival prediction

Reference 21

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This paper cites Label-Efficient Deep Learning in Medical Image Analysis: Challenges and Future Directions.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification Label-Efficient Deep Learning in Medical Image Analysis: Challenges and Future Directions

Reference 22

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This paper cites Dual-stream multiple instance learning network for whole slide image classifica- tion with self-supervised contrastive learning.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification Dual-stream multiple instance learning network for whole slide image classifica- tion with self-supervised contrastive learning

Reference 23

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Observation 9296817e-24f0-4596-b215-80ea70ebb786 · outbound

This paper cites Dt-mil: deformable transformer for multi-instance learning on histopathological image.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification Dt-mil: deformable transformer for multi-instance learning on histopathological image

Reference 24

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Observation 7152ba35-239d-4c5b-a37f-81e9521bd28e · outbound

This paper cites Dynamic graph repre- sentation with knowledge-aware attention for histopathology whole slide image analysis.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification Dynamic graph repre- sentation with knowledge-aware attention for histopathology whole slide image analysis

Reference 25

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Observation 80b178e6-464a-4140-a1c9-496bb98fc9b6 · outbound

This paper cites Interventional bag multi-instance learning on whole-slide pathological images.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification Interventional bag multi-instance learning on whole-slide pathological images

Reference 26

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Observation 03585620-417e-477a-862a-e4611a36f2fa · outbound

This paper cites Data-efficient and weakly supervised computational pathology on whole- slide images.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification Data-efficient and weakly supervised computational pathology on whole- slide images

Reference 27

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This paper cites Visual language pre- trained multiple instance zero-shot transfer for histopathol- ogy images.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification Visual language pre- trained multiple instance zero-shot transfer for histopathol- ogy images

Reference 28

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Observation 87cddffe-a036-46ab-bc8e-c43f30a3b6bd · outbound

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

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification A visual- language foundation model for computational pathology

Reference 29

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Observation c5245d8f-041a-428d-b687-deb579ddc2df · outbound

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

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification Towards A Generalizable Pathology Foundation Model via Unified Knowledge Distillation

Reference 30

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This paper cites Digital pathology and artificial intelli- gence.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification Digital pathology and artificial intelli- gence

Reference 31

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This paper cites The rise of ai language pathologists: Exploring two-level prompt learning for few-shot weakly-supervised whole slide image classification.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification The rise of ai language pathologists: Exploring two-level prompt learning for few-shot weakly-supervised whole slide image classification

Reference 32

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This paper cites Pathology-knowledge Enhanced Multi-instance Prompt Learning for Few-shot Whole Slide Image Classification.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification Pathology-knowledge Enhanced Multi-instance Prompt Learning for Few-shot Whole Slide Image Classification

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FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification Transmil: Transformer based correlated multiple instance learning for whole slide image classification

Reference 34

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FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification Vila-mil: Dual-scale vision-language multiple instance learning for whole slide image classification

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This paper cites Mor- phological prototyping for unsupervised slide representation learning in computational pathology.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification Mor- phological prototyping for unsupervised slide representation learning in computational pathology

Reference 36

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This paper cites Song, Richard J.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification Song, Richard J

Reference 37

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This paper cites A comprehensive survey of few-shot learning: Evolution, applications, challenges, and opportu- nities.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification A comprehensive survey of few-shot learning: Evolution, applications, challenges, and opportu- nities

Reference 38

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This paper cites Review the cancer genome atlas (tcga): an im- measurable source of knowledge.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification Review the cancer genome atlas (tcga): an im- measurable source of knowledge

Reference 39

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This paper cites Deep learning in histopathology: the path to the clinic.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification Deep learning in histopathology: the path to the clinic

Reference 40

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

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification A foundation model for clinical-grade computational pathology and rare cancers detection

Reference 41

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FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification Scl-wc: Cross-slide contrastive learning for weakly-supervised whole-slide image classifi- cation

Reference 42

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This paper cites A pathology foundation model for can- cer diagnosis and prognosis prediction.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification A pathology foundation model for can- cer diagnosis and prognosis prediction

Reference 43

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This paper cites Dsnet: A dual-stream framework for weakly- supervised gigapixel pathology image analysis.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification Dsnet: A dual-stream framework for weakly- supervised gigapixel pathology image analysis

Reference 44

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FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification Unresolved cited work

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

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification A whole-slide foundation model for digital pathology from real-world data

Reference 48

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Observation fc6d3d72-d4f8-4b46-ab27-0f0ea436dbab · outbound

This paper cites Multimodal optimal transport- based co-attention transformer with global structure con- sistency for survival prediction.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification Multimodal optimal transport- based co-attention transformer with global structure con- sistency for survival prediction

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:01:10.340605Z

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

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification A Multimodal Knowledge-enhanced Whole-slide Pathology Foundation Model

Reference 50

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This paper cites Towards better understanding and better generalization of few-shot classification in histology images with contrastive learning.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification Towards better understanding and better generalization of few-shot classification in histology images with contrastive learning

Reference 51

Resolution: verified exact; local_arxiv, observed 2026-08-12T15:01:09.877588Z

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Observation 9489fad0-d09b-49ed-a218-d9cda39a3423 · outbound

This paper cites Mambamil: En- hancing long sequence modeling with sequence reordering in computational pathology.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification Mambamil: En- hancing long sequence modeling with sequence reordering in computational pathology

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:01:10.320678Z

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Observation 5fc401cd-c6f1-4d14-8e79-eee9b23b16d8 · outbound

This paper cites Prototypical multiple instance learning for predicting lymph node metastasis of breast cancer from whole-slide pathological images.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification Prototypical multiple instance learning for predicting lymph node metastasis of breast cancer from whole-slide pathological images

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:01:10.302209Z

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Observation 77aad429-b23a-4657-ba63-5fedd7e9efd7 · outbound

This paper cites Dtfd- mil: Double-tier feature distillation multiple instance learn- ing for histopathology whole slide image classification.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification Dtfd- mil: Double-tier feature distillation multiple instance learn- ing for histopathology whole slide image classification

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:01:10.281483Z

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Observation 040cc5b2-62ad-4899-9a05-34c623df5edb · outbound

This paper cites Prototypical Information Bottlenecking and Disentangling for Multimodal Cancer Survival Prediction.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification Prototypical Information Bottlenecking and Disentangling for Multimodal Cancer Survival Prediction

Reference 55

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Observation 05b16bfd-3b2e-45d9-ae93-376b54ac3054 · outbound

This paper cites Diffusion-based Virtual Staining from Polarimetric Mueller Matrix Imaging.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification Diffusion-based Virtual Staining from Polarimetric Mueller Matrix Imaging

Reference 56

Resolution: verified exact; local_arxiv, observed 2026-08-12T15:01:09.833832Z

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Observation 9d2f904c-c7f8-458b-bd75-7f8dce5ec4cb · outbound

This paper cites A graph-transformer for whole slide image classifica- tion.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification A graph-transformer for whole slide image classifica- tion

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:01:10.262813Z

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Observation 87b31907-083f-4483-ae29-1cd2a1046175 · outbound

This paper cites Cross-modal translation and alignment for survival analysis.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification Cross-modal translation and alignment for survival analysis

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:01:10.245861Z

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Observation 27192cd4-3e88-46b7-805a-2f7712ce281b · outbound

This paper cites Learning to prompt for vision-language models.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification Learning to prompt for vision-language models

Reference 59

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Observation 9de7793e-f9af-4cbc-b6af-ec846b2991fe · outbound

This paper cites large polygonal cells with clear cytoplasm.

FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification large polygonal cells with clear cytoplasm

Reference 2022

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:01:10.217074Z

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Pith citing papers

Observation 7b47d81b-098e-4bce-8dbe-ed5334c8de53 · inbound

VLM-based Prompts as the Optimal Assistant for Unpaired Histopathology Virtual Staining cites this paper.

VLM-based Prompts as the Optimal Assistant for Unpaired Histopathology Virtual Staining FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-08-16T11:29:49.442162Z

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