SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification | Paper Citation Record

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This paper cites Deep residual learning for image recognition.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification Deep residual learning for image recognition

Reference 1

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Observation 82a25df3-b958-41a8-a3ae-0a13ec19cee1 · outbound

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

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification Transmil: Transformer based correlated multiple instance learning for whole slide image classification

Reference 2

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Observation f8dccd33-9d21-46f9-8094-80c0bd9b9db6 · outbound

This paper cites Feature re-embedding: Towards foundation model- level performance in computational pathology.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification Feature re-embedding: Towards foundation model- level performance in computational pathology

Reference 3

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Observation b24d652f-9c45-4d74-a47d-4d3de200c058 · outbound

This paper cites Conditional Positional Encodings for Vision Transformers.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification Conditional Positional Encodings for Vision Transformers

Reference 4

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Observation fc063572-b648-45df-a487-9131604bea30 · outbound

This paper cites Roformer: Enhanced transformer with rotary position embedding.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification Roformer: Enhanced transformer with rotary position embedding

Reference 5

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Observation 7a061afa-fbd8-4705-9219-8fa15cffed38 · outbound

This paper cites Unified-IO 2: Scaling autoregressive multimodal models with vision language audio and action.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification Unified-IO 2: Scaling autoregressive multimodal models with vision language audio and action

Reference 7

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Observation 8f0c6251-da50-495f-9eaa-cdea8cde2749 · outbound

This paper cites CycleMLP: A MLP-like Architecture for Dense Prediction.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification CycleMLP: A MLP-like Architecture for Dense Prediction

Reference 9

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Observation ce528d0e-4e49-4946-a949-c5790b2f88e1 · outbound

This paper cites ChordMixer: A Scalable Neural Attention Model for Sequences with Different Lengths.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification ChordMixer: A Scalable Neural Attention Model for Sequences with Different Lengths

Reference 10

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Observation 58236221-2e33-4b66-8923-1fff05267a72 · outbound

This paper cites Metaformer is actually what you need for vision.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification Metaformer is actually what you need for vision

Reference 11

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Observation 545ce4fe-6415-4cb3-af82-2b1995956501 · outbound

This paper cites Shapley values-enabled progressive pseudo bag augmentation for whole-slide image classification.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification Shapley values-enabled progressive pseudo bag augmentation for whole-slide image classification

Reference 12

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Observation 74f75715-9878-4ed7-820e-7415171748cc · outbound

This paper cites Patch-based convolutional neural network for whole slide tissue image classification.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification Patch-based convolutional neural network for whole slide tissue image classification

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:37:08.457992Z

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Observation eb6ac842-095b-4e03-8008-3d69ffee189b · outbound

This paper cites Eliceiri.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification Eliceiri

Reference 14

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Observation 00968bab-2f24-46fd-b50c-f233863fd233 · outbound

This paper cites Lu et al.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification Lu et al

Reference 15

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Observation 73845feb-939a-49b5-a923-bb7f2a66dfbe · outbound

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

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification Dtfd-mil: Double-tier feature distillation multiple instance learning for histopathology whole slide image classification

Reference 16

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Observation 942b2ac0-a98e-4842-a21f-0c3f3120232d · outbound

This paper cites Chen et al.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification Chen et al

Reference 17

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Observation 08369ed7-560a-4fbf-8eb0-810ae652c00b · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 18

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Observation 954aa85d-4a10-457a-a576-f7efc051e859 · outbound

This paper cites Self-Attention with Relative Position Representations.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification Self-Attention with Relative Position Representations

Reference 19

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Observation 8625ece4-3bfe-4c38-a047-ae67fffb7106 · outbound

This paper cites Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context

Reference 20

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Observation 366d9521-9dc7-440b-97b1-6c5c11e6734b · outbound

This paper cites Transformers are rnns: Fast autoregressive transformers with linear attention.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification Transformers are rnns: Fast autoregressive transformers with linear attention

Reference 21

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Observation d4433c27-d984-4b20-ab49-ce488e05a076 · outbound

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

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification A whole-slide foundation model for digital pathology from real-world data

Reference 22

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Observation c4a1aa82-ae84-4f8a-b47f-ca6553bbec57 · outbound

This paper cites Norma: A noise robust memory-augmented framework for whole slide image classification.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification Norma: A noise robust memory-augmented framework for whole slide image classification

Reference 23

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Observation d0b759b8-8667-4b19-97e6-e1b5133063eb · outbound

This paper cites Vaswani et al.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification Vaswani et al

Reference 24

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Observation cd673b8e-6971-4afb-937a-41480f9f2bd1 · outbound

This paper cites Efficiently Modeling Long Sequences with Structured State Spaces.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification Efficiently Modeling Long Sequences with Structured State Spaces

Reference 25

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Observation 4c1ff521-f3df-42b9-b7d1-928c8de4fb47 · outbound

This paper cites Sparse factorization of square matrices with application to neural attention modeling.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification Sparse factorization of square matrices with application to neural attention modeling

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:37:06.482940Z

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Observation a4e31c2c-8203-4eb2-a0fe-bf9dfbaf976e · outbound

This paper cites Mambamil: Enhancing long sequence modeling with sequence reordering in computational pathol- ogy.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification Mambamil: Enhancing long sequence modeling with sequence reordering in computational pathol- ogy

Reference 27

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Observation ebaf92a0-f4a7-431b-909d-65c3e084c3d4 · outbound

This paper cites MamMIL: Multiple Instance Learning for Whole Slide Images with State Space Models.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification MamMIL: Multiple Instance Learning for Whole Slide Images with State Space Models

Reference 28

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Observation 248df77b-31a0-45cd-a297-705c3d9191f9 · outbound

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

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification Clinical-grade computational pathology using weakly supervised deep learning on whole slide images

Reference 29

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Observation a9269da4-c825-4723-9da9-45c1bb5e9b52 · outbound

This paper cites Mamba: Linear-Time Sequence Modeling with Selective State Spaces.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 30

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Observation 8ecd8f01-ca9f-4eed-8134-dfe550d6fd4c · outbound

This paper cites Structured state space models for multiple instance learning in digital pathology.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification Structured state space models for multiple instance learning in digital pathology

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:37:05.656620Z

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Observation e9aa2968-61cd-4e6d-8c21-a2657cdc1eed · outbound

This paper cites The farthest point strategy for progressive image sampling.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification The farthest point strategy for progressive image sampling

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:37:05.504041Z

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Observation ab7e7183-aa3b-4059-b7ba-86836f90455b · outbound

This paper cites Rotary position embedding for vision transformer.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification Rotary position embedding for vision transformer

Reference 33

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Observation 916169ce-a29e-4382-9e51-70d15fbdde50 · outbound

This paper cites FiT: Flexible Vision Transformer for Diffusion Model.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification FiT: Flexible Vision Transformer for Diffusion Model

Reference 34

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Observation 7bbfa68b-7b30-4134-b810-93a9aae03c23 · outbound

This paper cites Tolstikhin et al.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification Tolstikhin et al

Reference 35

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Observation ca1f90af-c710-4dbd-ac6b-e749babef3d9 · outbound

This paper cites Attention-based deep multiple instance learning.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification Attention-based deep multiple instance learning

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:37:05.184002Z

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Observation 9d4964bf-2483-48db-b4e5-8fdf292d3dce · outbound

This paper cites Nystromformer: A nystrom-based algorithm for approximating self-attention.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification Nystromformer: A nystrom-based algorithm for approximating self-attention

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:37:04.973931Z

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Observation d8d62bac-c4d8-45d1-9899-e556db3a430c · outbound

This paper cites Rethinking Transformer for Long Contextual Histopathology Whole Slide Image Analysis.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification Rethinking Transformer for Long Contextual Histopathology Whole Slide Image Analysis

Reference 38

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Observation 62ce59f6-f3bb-4ffe-8573-e2249103063a · outbound

This paper cites LongNet: Scaling Transformers to 1,000,000,000 Tokens.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification LongNet: Scaling Transformers to 1,000,000,000 Tokens

Reference 39

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Observation b458e626-8b96-40bc-ba08-f11a4ef333fb · outbound

This paper cites A Length-Extrapolatable Transformer.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification A Length-Extrapolatable Transformer

Reference 40

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Observation e29a5a25-1c8d-42b4-b498-b68f606a6ef5 · outbound

This paper cites Pay attention to mlps.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification Pay attention to mlps

Reference 42

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Observation f8685816-2a40-4f03-b274-e4d44569dc32 · outbound

This paper cites Deformable convolutional networks.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification Deformable convolutional networks

Reference 43

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Observation dc65f01a-8690-4346-979c-031edb5505f1 · outbound

This paper cites Task-specific fine-tuning via variational information bottleneck for weakly-supervised pathology whole slide image classifi- cation.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification Task-specific fine-tuning via variational information bottleneck for weakly-supervised pathology whole slide image classifi- cation

Reference 44

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Observation b79a55e9-e116-41a4-928e-8dca2aab1990 · outbound

This paper cites Multiple instance learning framework with masked hard instance mining for whole slide image classification.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification Multiple instance learning framework with masked hard instance mining for whole slide image classification

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:37:04.144689Z

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Observation 08f93b06-906b-4f6c-b0e2-c5f4fc8c4eb8 · outbound

This paper cites Histopathology whole slide image analysis with heterogeneous graph representation learning.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification Histopathology whole slide image analysis with heterogeneous graph representation learning

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:37:04.009027Z

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Observation 0c6fe84e-73cc-482d-bfeb-178a15424e50 · outbound

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

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification A graph-transformer for whole slide image classification

Reference 47

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Observation 6716ad2c-4f62-44ab-af69-3e7aaa53654b · outbound

This paper cites Chen et al.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification Chen et al

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:37:03.643605Z

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Observation 5877cc7b-57c1-457f-922a-d29f581c46a8 · outbound

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

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer

Reference 49

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Observation e0c364b8-4f30-4d6b-aca9-8061fa135833 · outbound

This paper cites Smith, and Mike Lewis.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification Smith, and Mike Lewis

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:37:03.019293Z

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Observation 4de3ef66-126d-43f8-9495-d5e2a3336e8e · outbound

This paper cites Flashattention: Fast and memory-efficient exact attention with io-awareness.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification Flashattention: Fast and memory-efficient exact attention with io-awareness

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:37:02.833848Z

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Observation 60032fe4-dde8-4b6d-8550-9488b6e9136e · outbound

This paper cites Resmlp: Feedforward networks for image classifica- tion with data-efficient training.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification Resmlp: Feedforward networks for image classifica- tion with data-efficient training

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:37:02.684853Z

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Observation 82300655-8129-4d56-a101-f05e447da938 · outbound

This paper cites an unresolved cited work.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification Unresolved cited work

Reference 53

Resolution: unresolved; raw_fallback, observed 2026-08-05T10:37:02.483550Z

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This paper cites Vision permutator: A permutable mlp-like architecture for visual recognition.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification Vision permutator: A permutable mlp-like architecture for visual recognition

Reference 54

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This paper cites An image patch is a wave: Phase-aware vision mlp.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification An image patch is a wave: Phase-aware vision mlp

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:37:02.236591Z

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This paper cites Global filter networks for image classification.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification Global filter networks for image classification

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:37:02.006811Z

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Observation c11d8840-6e21-45a6-b779-09c5a278f463 · outbound

This paper cites Extending Context Window of Large Language Models via Positional Interpolation.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification Extending Context Window of Large Language Models via Positional Interpolation

Reference 57

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Observation aac9e6aa-73fb-4c48-bbde-da3df8653c30 · outbound

This paper cites Delving deep into rectifiers: Surpassing human-level performance on imagenet classification.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification Delving deep into rectifiers: Surpassing human-level performance on imagenet classification

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:37:01.842338Z

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Observation fc4a76fa-d4bc-41db-9ce4-ba949564e3ea · outbound

This paper cites COVID-19 pandemic and managing supply chain risks: NVIDIA’s graphics card shortage case analysis, 2021.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification COVID-19 pandemic and managing supply chain risks: NVIDIA’s graphics card shortage case analysis, 2021

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:37:01.615103Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 44b1168b-a46c-4975-91e6-fe06e855b81d · outbound

This paper cites NVIDIA’s bet on artificial intelligence: The impact on healthcare.

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification NVIDIA’s bet on artificial intelligence: The impact on healthcare

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:37:01.382636Z

Source-reported events for the cited work

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