Paper Citation Record · LEDGER

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba

As of 12 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 1 inbound Pith citation observation for arXiv:2412.16711.

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

pith.paper-citation-record.v1
2412.16711 v1

Coverage vector

measured 54 of 54 reference resolution

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measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T21:17:37.867356Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-10T21:17:37.979229Z

Reference resolution

54 of 54 outbound references displayed

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External citation measurements

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Outbound references

Observation c86ee619-8697-46b6-927b-38420ad4a25c · outbound

This paper cites An image is worth 16x16 words: Trans- formers for image recognition at scale.

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba An image is worth 16x16 words: Trans- formers for image recognition at scale

Reference 1

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Observation 07c9cfff-6756-4bc9-979a-9f64a8c2f8b4 · outbound

This paper cites Tertiary lymphoid structures (tls) identification and density assessment on h&e- stained digital slides of lung cancer.

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba Tertiary lymphoid structures (tls) identification and density assessment on h&e- stained digital slides of lung cancer

Reference 2

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Observation 67da57a8-d783-456f-b82d-25727c2b1d29 · outbound

This paper cites Scaling vision transformers to gigapixel images via hierarchical self-supervised learning.

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba Scaling vision transformers to gigapixel images via hierarchical self-supervised learning

Reference 3

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Observation b17ad5a1-e0e6-4bc6-8ece-50ffca7c38a4 · outbound

This paper cites Scaling vision transformers to gigapixel images via hierarchical self-supervised learning.

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba Scaling vision transformers to gigapixel images via hierarchical self-supervised learning

Reference 4

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Observation 3d090d92-b2fc-4e48-9334-6fd2e726598a · outbound

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

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba Towards a general-purpose foundation model for com- putational pathology

Reference 5

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Observation 06d5c5a3-34eb-4e56-8b81-13bb340c168f · outbound

This paper cites Diagnose like a pathologist: Weakly-supervised pathologist-tree network for slide-level immunohistochemical scoring.

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba Diagnose like a pathologist: Weakly-supervised pathologist-tree network for slide-level immunohistochemical scoring

Reference 6

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Observation 87b5335c-cf7a-44c4-85b9-fe395dbc95ad · outbound

This paper cites Spatial architecture and arrangement of tumor-infiltrating lympho- cytes for predicting likelihood of recurrence in early-stage non–small cell lung cancer.

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba Spatial architecture and arrangement of tumor-infiltrating lympho- cytes for predicting likelihood of recurrence in early-stage non–small cell lung cancer

Reference 7

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Observation a7ed2e7c-7dd6-41f1-a42e-a04a53653182 · outbound

This paper cites Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality.

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality

Reference 8

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Observation 5a9805c1-7b84-4863-8031-5aa8af1910a0 · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba Imagenet: A large-scale hierarchical image database

Reference 9

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Observation e608ed9f-03de-4dd6-a1fe-10e21d8f6ad8 · outbound

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

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba LongNet: Scaling Transformers to 1,000,000,000 Tokens

Reference 10

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Observation d5bc601c-7673-4835-b823-f5cbac0d1e76 · outbound

This paper cites Structured state space models for multiple instance learning in digital pathol- ogy.

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba Structured state space models for multiple instance learning in digital pathol- ogy

Reference 11

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Observation 4bcde266-5651-4e28-ae09-4c2df38f6209 · outbound

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

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 12

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Observation a276929b-163d-4985-aaad-d1fb2c1840e9 · outbound

This paper cites Multi-scale domain-adversarial multiple-instance cnn for cancer subtype classification with unannotated histopatho- logical images.

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba Multi-scale domain-adversarial multiple-instance cnn for cancer subtype classification with unannotated histopatho- logical images

Reference 13

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Observation 0c0dff7e-cc9d-408a-8d7a-fad406c7c198 · outbound

This paper cites Deep residual learning for image recognition.

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba Deep residual learning for image recognition

Reference 14

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Observation 70b87d98-7238-4b55-8475-c5ca7a469697 · outbound

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

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba Hˆ 2-mil: ex- ploring hierarchical representation with heterogeneous mul- tiple instance learning for whole slide image analysis

Reference 15

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Observation 314e8de9-4ed9-4e59-a6db-8f93e5a3bdfa · outbound

This paper cites LocalMamba: Visual State Space Model with Windowed Selective Scan.

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba LocalMamba: Visual State Space Model with Windowed Selective Scan

Reference 16

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This paper cites Integration of patch features through self-supervised learning and transformer for survival analysis on whole slide images.

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba Integration of patch features through self-supervised learning and transformer for survival analysis on whole slide images

Reference 17

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Observation bbbc7c0e-ca46-4cec-b8df-7b04d5afce2a · outbound

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

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba A visual–language foundation model for pathology image analysis using medical twitter

Reference 18

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This paper cites Attention-based deep multiple instance learning.

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba Attention-based deep multiple instance learning

Reference 19

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Observation 27fde124-55c8-473c-8020-9d09334d5ac4 · outbound

This paper cites HEST-1k: A Dataset for Spatial Transcriptomics and Histology Image Analysis.

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba HEST-1k: A Dataset for Spatial Transcriptomics and Histology Image Analysis

Reference 20

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Observation 0fc1d6e3-0620-40b4-8be1-c07e2201cc68 · outbound

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From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba Self-path: Self-supervision for classification of pathology images with limited annotations

Reference 21

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Observation 26212b39-1b43-4922-8f3b-a650562672e5 · outbound

This paper cites Dual-stream multi- ple instance learning network for whole slide image classi- fication with self-supervised contrastive learning.

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba Dual-stream multi- ple instance learning network for whole slide image classi- fication with self-supervised contrastive learning

Reference 22

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Observation 20dbd6d0-0568-4aa6-9236-ca750f828147 · outbound

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

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba Dynamic graph repre- sentation with knowledge-aware attention for histopathology whole slide image analysis

Reference 23

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Observation 1da60956-1807-4707-bb00-f2da6333009e · outbound

This paper cites VMamba: Visual State Space Model.

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba VMamba: Visual State Space Model

Reference 24

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This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba Swin transformer: Hierarchical vision transformer using shifted windows

Reference 25

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

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba Data-efficient and weakly supervised computational pathology on whole- slide images

Reference 26

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Observation 063ab99d-0af5-4603-b589-5e0ba5418e7a · outbound

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

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba A visual- language foundation model for computational pathology

Reference 27

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Observation 4064ae6d-3488-4178-b0d8-58abbc2f02a4 · outbound

This paper cites Self-distillation augmented masked autoen- coders for histopathological image understanding.

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba Self-distillation augmented masked autoen- coders for histopathological image understanding

Reference 28

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Observation e1a00d00-acb3-4f0d-8042-e8b35ddf3313 · outbound

This paper cites Vim4path: Self-supervised vision mamba for histopathology images.

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba Vim4path: Self-supervised vision mamba for histopathology images

Reference 29

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Observation faecf991-a70a-4279-8631-3c002bed8aa5 · outbound

This paper cites S4nd: Modeling images and videos as multidimensional signals with state spaces.

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba S4nd: Modeling images and videos as multidimensional signals with state spaces

Reference 30

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This paper cites Ivt: An end-to-end instance-guided video transformer for 3d pose estimation.

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba Ivt: An end-to-end instance-guided video transformer for 3d pose estimation

Reference 31

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Observation 6411f3fb-842e-4131-9c46-805c229aeda4 · outbound

This paper cites Learning degradation-robust spatiotemporal frequency-transformer for video super- resolution.

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba Learning degradation-robust spatiotemporal frequency-transformer for video super- resolution

Reference 32

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Observation f6842073-7976-4290-8f0b-cbe6c09771f6 · outbound

This paper cites End-to-end Multi-source Visual Prompt Tuning for Survival Analysis in Whole Slide Images.

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba End-to-end Multi-source Visual Prompt Tuning for Survival Analysis in Whole Slide Images

Reference 33

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Observation ca7b5dc6-3657-46dd-a83f-96d354be1cc8 · outbound

This paper cites Global contrast-masked autoencoders are powerful pathological representation learners.

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba Global contrast-masked autoencoders are powerful pathological representation learners

Reference 34

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Observation 8f39b28a-a91a-4c5b-a179-5b8f6a403417 · outbound

This paper cites Spatial organization and molecular correlation of tumor-infiltrating lymphocytes using deep learning on pathology images.

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba Spatial organization and molecular correlation of tumor-infiltrating lymphocytes using deep learning on pathology images

Reference 35

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Observation a67b49a0-fb96-47c0-bfa3-82b0c032b2d2 · outbound

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

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba Transmil: Transformer based correlated multiple instance learning for whole slide image classification

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:23:55.665880Z

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Observation e4d55601-97f1-4ae6-adb1-90137e6d22db · outbound

This paper cites Adaptive weighting multi-field-of-view cnn for semantic segmentation in pathology.

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba Adaptive weighting multi-field-of-view cnn for semantic segmentation in pathology

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:23:55.634669Z

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Observation 31fd8b0b-7b38-40c5-a25e-393d5d67dd5c · outbound

This paper cites Training data-efficient image transformers & distillation through at- tention.

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba Training data-efficient image transformers & distillation through at- tention

Reference 38

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Observation a73ae2c9-b1fc-4f4a-b369-e900e6ad9345 · outbound

This paper cites Multi-resolution deep learning characterizes tertiary lymphoid structures and their prognostic relevance in solid tumors.

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba Multi-resolution deep learning characterizes tertiary lymphoid structures and their prognostic relevance in solid tumors

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:23:55.575897Z

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Observation 9029dfe7-55f6-4f3c-b94b-7e63fb341e58 · outbound

This paper cites Rethinking multiple instance learning for whole slide image classification: A bag-level classifier is a good instance-level teacher.

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba Rethinking multiple instance learning for whole slide image classification: A bag-level classifier is a good instance-level teacher

Reference 40

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Observation ef769229-6a3b-4771-abf2-0cdbf4981aac · outbound

This paper cites When an Image is Worth 1,024 x 1,024 Words: A Case Study in Computational Pathology.

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba When an Image is Worth 1,024 x 1,024 Words: A Case Study in Computational Pathology

Reference 41

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Observation e83c36cd-893d-4d7d-8c56-9f64186ceeae · outbound

This paper cites Transpath: Transformer-based self-supervised learning for histopatho- logical image classification.

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba Transpath: Transformer-based self-supervised learning for histopatho- logical image classification

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:23:55.525659Z

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Observation 72b685b3-653c-4f82-8e73-a9ad693ce373 · outbound

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

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba A pathology foundation model for can- cer diagnosis and prognosis prediction

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:23:55.500496Z

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Observation 70b4be56-79ef-4f91-90e0-e24c7038e496 · outbound

This paper cites Exploring low-rank property in multiple instance learning for whole slide image classifica- tion.

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba Exploring low-rank property in multiple instance learning for whole slide image classifica- tion

Reference 44

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Observation 5b4c633b-e6b0-4fbc-bd2e-6d7530393cf3 · outbound

This paper cites Aggregated residual transformations for deep neural networks.

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba Aggregated residual transformations for deep neural networks

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:23:55.458662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation f43778aa-9702-4e67-ba1e-b73dadef891c · outbound

This paper cites Diagnose Like a Pathologist: Transformer-Enabled Hierarchical Attention-Guided Multiple Instance Learning for Whole Slide Image Classification.

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba Diagnose Like a Pathologist: Transformer-Enabled Hierarchical Attention-Guided Multiple Instance Learning for Whole Slide Image Classification

Reference 46

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Observation 2dcffebb-95ee-4efc-8d3d-e832e7ebff62 · outbound

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

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba A whole-slide foundation model for digital pathology from real-world data

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:23:55.420828Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 917a1748-3532-4018-be65-6bcfe51ca4f8 · outbound

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

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba A whole-slide foundation model for digital pathology from real-world data

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:23:55.384475Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation bac2c980-41a9-4ccb-82cc-96eeaef29587 · outbound

This paper cites Self-supervised visual representation learn- ing for histopathological images.

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba Self-supervised visual representation learn- ing for histopathological images

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:23:55.342278Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 452c06e8-13d5-4eaa-b7ff-a8c8d2d56774 · outbound

This paper cites MambaMIL: Enhancing Long Sequence Modeling with Sequence Reordering in Computational Pathology.

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba MambaMIL: Enhancing Long Sequence Modeling with Sequence Reordering in Computational Pathology

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-11T10:23:54.902860Z

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Observation 9ca51f9b-d16e-4b99-96e1-c41daf6a0887 · outbound

This paper cites Whole slide images based cancer survival prediction using attention guided deep mul- tiple instance learning networks.

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba Whole slide images based cancer survival prediction using attention guided deep mul- tiple instance learning networks

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:23:55.309894Z

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Observation cb9c4b16-299d-499d-8d3b-6ee2a9597df9 · outbound

This paper cites Bias in cross- entropy-based training of deep survival networks.

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba Bias in cross- entropy-based training of deep survival networks

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:23:55.284643Z

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Observation 198e05d0-5acf-40b0-bdfd-6e3731503563 · outbound

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

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba Dtfd- mil: Double-tier feature distillation multiple instance learn- ing for histopathology whole slide image classification

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:23:55.263133Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation a4d5cf60-e630-4fdb-a971-7d803b4a7f56 · outbound

This paper cites Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model.

From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-11T10:23:54.926898Z

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Pith citing papers

Observation dab27af3-1e28-491c-9b6e-b6be160279c0 · inbound

Atlas: A Novel Pathology Foundation Model by Mayo Clinic, Charit\'e, and Aignostics cites this paper.

Atlas: A Novel Pathology Foundation Model by Mayo Clinic, Charit\'e, and Aignostics From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba

Reference 32

Resolution: verified exact; local_arxiv, observed 2026-08-10T21:17:37.986512Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.