Paper Citation Record · LEDGER

Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis

As of 17 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 1 inbound Pith citation observation for arXiv:2511.18089.

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

pith.paper-citation-record.v1
2511.18089 v2

Coverage vector

measured 53 of 53 reference resolution

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measured 54 of 54 standing notices

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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 2026-05-12T03:45:05.990528Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T07:06:35.270451Z

Reference resolution

53 of 53 outbound references displayed

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External citation measurements

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Outbound references

Observation 00a1cd84-a2dd-4944-98b4-7b87ede5312d · outbound

This paper cites Multimodal biomedical ai.Nature Medicine, 28(9):1773–1784, 2022.

Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis Multimodal biomedical ai.Nature Medicine, 28(9):1773–1784, 2022

Reference 1

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Observation 6e5333b8-2074-4c0a-a003-a92c61672e44 · outbound

This paper cites The logrank test.

Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis The logrank test

Reference 2

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Observation 74c4129d-03a3-4b64-a8a1-9229a0d18a38 · outbound

This paper cites Par- tial optimal tranport with applications on positive-unlabeled learning.Advances in Neural Information Processing Sys- tems, 33:2903–2913, 2020.

Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis Par- tial optimal tranport with applications on positive-unlabeled learning.Advances in Neural Information Processing Sys- tems, 33:2903–2913, 2020

Reference 3

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Observation f4c84e3f-652d-407e-8d56-fb91602e1c60 · outbound

This paper cites Graph optimal transport for cross-domain alignment.

Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis Graph optimal transport for cross-domain alignment

Reference 4

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Observation 38805984-d445-4c7a-b1f1-ca98fd414947 · outbound

This paper cites an unresolved cited work.

Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis Unresolved cited work

Reference 5

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Observation fcfd3d83-002d-4a31-9d50-2d0f3d617795 · outbound

This paper cites Whole slide images are 2d point clouds: Context-aware survival prediction using patch-based graph convolutional networks.

Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis Whole slide images are 2d point clouds: Context-aware survival prediction using patch-based graph convolutional networks

Reference 6

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Observation 2b4e15b2-ec3a-4e84-ac5b-762f343c7896 · outbound

This paper cites Multimodal co-attention transformer for survival prediction in gigapixel whole slide images.

Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis Multimodal co-attention transformer for survival prediction in gigapixel whole slide images

Reference 7

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Observation cbd1157a-b31e-4c17-a3c9-a32b77386282 · outbound

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

Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis Scaling vision transformers to gigapixel images via hierarchical self-supervised learning

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Observation 274ed36b-8221-4db1-a84b-7b75efec74d1 · outbound

This paper cites Pan-cancer in- tegrative histology-genomic analysis via multimodal deep learning.Cancer Cell, 40(8):865–878, 2022.

Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis Pan-cancer in- tegrative histology-genomic analysis via multimodal deep learning.Cancer Cell, 40(8):865–878, 2022

Reference 9

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Observation 703633b5-5af1-41cd-914e-eabe2ae2abae · outbound

This paper cites Towards a general-purpose foundation model for com- putational pathology.Nature Medicine, 2024.

Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis Towards a general-purpose foundation model for com- putational pathology.Nature Medicine, 2024

Reference 10

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Observation e3238d9d-9bb8-478b-9dd7-cce795a16b5c · outbound

This paper cites Chen, Tong Ding, Ming Y.

Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis Chen, Tong Ding, Ming Y

Reference 11

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Observation 7cd0ee12-6fd0-4899-aa4b-68c64e929670 · outbound

This paper cites Mapping the landscape of histomorphological cancer pheno- types using self-supervised learning on unannotated pathol- ogy slides.Nature Communications, 15(1):4596, 2024.

Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis Mapping the landscape of histomorphological cancer pheno- types using self-supervised learning on unannotated pathol- ogy slides.Nature Communications, 15(1):4596, 2024

Reference 12

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Observation d0a6005c-d206-45ad-8192-f14f73dc2817 · outbound

This paper cites Regression models and life-tables.Journal of the Royal Statistical Society: Series B (Methodological), 34 (2):187–202, 1972.

Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis Regression models and life-tables.Journal of the Royal Statistical Society: Series B (Methodological), 34 (2):187–202, 1972

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Observation 04dd6084-0e69-4024-b5ea-531e87dd66de · outbound

This paper cites Sinkhorn distances: Lightspeed computation of optimal transport.Advances in neural information pro- cessing systems, 26, 2013.

Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis Sinkhorn distances: Lightspeed computation of optimal transport.Advances in neural information pro- cessing systems, 26, 2013

Reference 14

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Observation a6bea80f-7a7f-4fcc-99c0-68f7e3828d55 · outbound

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

Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis Imagenet: A large-scale hierarchical image database

Reference 15

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Observation dbd95e3f-f503-49b0-893e-dbe865e7ef82 · outbound

This paper cites Pathology-and-genomics multimodal transformer for survival outcome prediction.

Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis Pathology-and-genomics multimodal transformer for survival outcome prediction

Reference 16

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Observation ac222c2d-832b-4756-9057-834bc6cfa40b · outbound

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

Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis An image is worth 16x16 words: Transformers for image recognition at scale

Reference 17

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Observation 721ec050-d70f-4251-9f10-68bc3e3c2710 · outbound

This paper cites Bio- logically informed deep neural network for prostate cancer discovery.Nature, 598(7880):348–352, 2021.

Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis Bio- logically informed deep neural network for prostate cancer discovery.Nature, 598(7880):348–352, 2021

Reference 18

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Observation a5dfd484-d6f2-45e2-a6be-700c42df3adf · outbound

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

Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis Cross-modal translation and alignment for sur- vival analysis

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Observation 5f763238-d471-4878-a8e8-f13ffc306c3e · outbound

This paper cites Prentice Hall PTR, 1998.

Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis Prentice Hall PTR, 1998

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Observation 906f697a-b8e8-402e-a41e-14563f0a407c · outbound

This paper cites The impact of site-specific digital histology signatures on deep learning model accuracy and bias.Nature communications, 12(1):4423, 2021.

Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis The impact of site-specific digital histology signatures on deep learning model accuracy and bias.Nature communications, 12(1):4423, 2021

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Observation 60ffd814-749b-4591-9a8d-779ea53e7d6d · outbound

This paper cites Attention-based deep multiple instance learning.

Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis Attention-based deep multiple instance learning

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Observation bae18983-28f9-428c-a8d9-6c674c408753 · outbound

This paper cites The single-cell pathology landscape of breast cancer.Nature, 578 (7796):615–620, 2020.

Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis The single-cell pathology landscape of breast cancer.Nature, 578 (7796):615–620, 2020

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Observation c598dd35-23bd-46f4-9580-776954f70415 · outbound

This paper cites an unresolved cited work.

Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis Unresolved cited work

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Observation dcad5e12-4b07-4eef-b556-11c71db9821c · outbound

This paper cites Survival analysis.Unpublished manuscript, Institute for Social and Economic Research, University of Essex, Colchester, UK, 42:54–56, 2005.

Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis Survival analysis.Unpublished manuscript, Institute for Social and Economic Research, University of Essex, Colchester, UK, 42:54–56, 2005

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Observation 29656936-e6c7-4bfe-84f5-13a345b192f1 · outbound

This paper cites Self-normalizing neural networks.Ad- vances in neural information processing systems, 30, 2017.

Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis Self-normalizing neural networks.Ad- vances in neural information processing systems, 30, 2017

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Observation 1baf6e35-faa6-4ffa-bf53-6e33a3e678a1 · outbound

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

Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis Dual-stream multiple instance learning network for whole slide image classifica- tion with self-supervised contrastive learning

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Observation 9b3ce5e7-2e82-4118-a370-ebcc87af51dc · outbound

This paper cites The molec- ular signatures database hallmark gene set collection.Cell systems, 1(6):417–425, 2015.

Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis The molec- ular signatures database hallmark gene set collection.Cell systems, 1(6):417–425, 2015

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Observation cabe449a-1604-4304-ae59-3bdbd7623382 · outbound

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Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis Interventional bag multi-instance learning on whole-slide pathological images

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Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis An integrated TCGA pan-cancer clinical data resource to drive high-quality survival outcome analyt- ics.Cell, 173(2):400–416, 2018

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Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis Data-efficient and weakly supervised computational pathology on whole- slide images.Nature biomedical engineering, 5(6):555–570,

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This paper cites Pre- dicting cancer outcomes from histology and genomics us- ing convolutional networks.Proceedings of the National Academy of Sciences, 115(13):E2970–E2979, 2018.

Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis Pre- dicting cancer outcomes from histology and genomics us- ing convolutional networks.Proceedings of the National Academy of Sciences, 115(13):E2970–E2979, 2018

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Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis Prognostic genome and transcriptome signatures in colorectal cancers

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Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis Representation Learning with Contrastive Predictive Coding

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Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis DINOv2: Learning Robust Visual Features without Supervision

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Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis Multimodal Cancer Survival Analysis via Hypergraph Learning with Cross-Modality Rebalance

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Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis Pathway enrichment analysis and visualization of omics data using g: Profiler, GSEA, Cytoscape and EnrichmentMap.Nature pro- tocols, 14(2):482–517, 2019

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Observation 505e066d-7c41-40b6-af92-37084b8123fb · outbound

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Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis Otsurv: A novel multiple instance learning framework for survival prediction with heterogeneity-aware optimal transport

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Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis High-dimensional survival anal- ysis: Methods and applications.Annual review of statistics and its application, 10:25–49, 2023

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Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis Transmil: Transformer based correlated multiple instance learning for whole slide image classification.Advances in neural information processing systems, 34:2136–2147, 2021

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Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis Hvtsurv: Hierarchical vision transformer for patient-level survival prediction from whole slide image

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Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis Mor- phological prototyping for unsupervised slide representation learning in computational pathology

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Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis Multimodal prototyping for cancer survival predic- tion

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Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis Attention is all you need.Advances in neural information processing systems, 30, 2017

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Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis Ahmed Raza, and Nasir Rajpoot

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Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis Multimodal optimal transport- based co-attention transformer with global structure con- sistency for survival prediction

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Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis Distilled prompt learning for incom- plete multimodal survival prediction

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Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis Mambamil: En- hancing long sequence modeling with sequence reordering in computational pathology

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Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis Whole slide images based cancer survival prediction using attention guided deep multi- ple instance learning networks.Medical Image Analysis, 65: 101789, 2020

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Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis Pˆ2ot: Progressive partial optimal transport for deep imbalanced clustering

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Observation b54abad5-9e54-4187-964a-3bf1607125fb · outbound

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Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis Dtfd- mil: Double-tier feature distillation multiple instance learn- ing for histopathology whole slide image classification

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This paper cites Prototypical information bottlenecking and dis- entangling for multimodal cancer survival prediction.

Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis Prototypical information bottlenecking and dis- entangling for multimodal cancer survival prediction

Reference 52

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This paper cites Robust Multimodal Survival Prediction with the Latent Differentiation Conditional Variational AutoEncoder.

Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis Robust Multimodal Survival Prediction with the Latent Differentiation Conditional Variational AutoEncoder

Reference 53

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Hystar: Hypernetwork-driven Style-adaptive Retrieval via Dynamic SVD Modulation cites this paper.

Hystar: Hypernetwork-driven Style-adaptive Retrieval via Dynamic SVD Modulation Together, Then Apart: Balancing Alignment and Distinctiveness for Multimodal Survival Analysis

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