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Paper Citation Record · LEDGER

Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis

As of 6 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 0 inbound Pith citation observations for arXiv:2512.01116.

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

pith.paper-citation-record.v1
2512.01116 v3

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-17T02:17:15.595874Z

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

26 of 26 outbound references displayed

  • verified exact9
  • verified fuzzy13
  • unresolved4
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e9a77c0a-7848-4f47-93a1-1d7709c8c53e · outbound

This paper cites Deep Variational Information Bottleneck.

Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis Deep Variational Information Bottleneck

Reference 1

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verified exact
arxiv_id, observed 2026-05-18T06:23:00.530339Z

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Observation 91008d40-ed90-4acf-8e56-3999502da03f · outbound

This paper cites The reactome pathway knowledgebase 2022.Nucleic acids research, 50(D1):D687–D692.

Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis The reactome pathway knowledgebase 2022.Nucleic acids research, 50(D1):D687–D692

Reference 2

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 1039267a-fc1c-459c-9b2d-8ce685f1be25 · outbound

This paper cites On the Binding Problem in Artificial Neural Networks.

Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis On the Binding Problem in Artificial Neural Networks

Reference 3

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verified exact
arxiv_id, observed 2026-05-17T02:18:52.550941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 4cce8392-d272-4f5e-82f1-e690780f897b · outbound

This paper cites Categorical Reparameterization with Gumbel-Softmax.

Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis Categorical Reparameterization with Gumbel-Softmax

Reference 4

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verified exact
local_arxiv, observed 2026-05-17T02:18:52.545883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation ae1cc5e1-9de9-452c-9069-e0b22c34195c · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis Adam: A Method for Stochastic Optimization

Reference 5

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verified exact
local_arxiv, observed 2026-05-17T02:18:52.541723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation fe8a11dd-8157-46be-98c8-651a3f4baacd · outbound

This paper cites Adaptive Prototype Learning for Multimodal Cancer Survival Analysis.

Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis Adaptive Prototype Learning for Multimodal Cancer Survival Analysis

Reference 6

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verified exact
arxiv_id, observed 2026-05-17T02:18:52.559855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation cedbeb5d-9bb0-405e-82d6-593ae920aab9 · outbound

This paper cites Multimodal Prototyping for cancer survival prediction.

Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis Multimodal Prototyping for cancer survival prediction

Reference 7

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verified exact
arxiv_id, observed 2026-05-17T02:18:52.537750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 5f15b631-fbe6-4cb8-a910-09868ca86490 · outbound

This paper cites The information bottleneck method.

Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis The information bottleneck method

Reference 8

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local_arxiv, observed 2026-05-17T02:18:52.533575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 7c8f79fc-b700-4cca-8191-2028aa0a0845 · outbound

This paper cites Prediction of recurrence risk in endometrial cancer with multimodal deep learning.Nature medicine, 30(7): 1962–1973.

Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis Prediction of recurrence risk in endometrial cancer with multimodal deep learning.Nature medicine, 30(7): 1962–1973

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation dad6812b-d42a-4af4-9f42-339a3dd358b2 · outbound

This paper cites AdaMHF: Adaptive Multimodal Hierarchical Fusion for Survival Prediction.

Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis AdaMHF: Adaptive Multimodal Hierarchical Fusion for Survival Prediction

Reference 10

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verified exact
arxiv_id, observed 2026-05-17T02:18:52.529890Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 276e5fe9-7ff2-4ce8-8fd6-45a35541de2b · outbound

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

Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis Prototypical Information Bottlenecking and Disentangling for Multimodal Cancer Survival Prediction

Reference 11

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verified exact
arxiv_id, observed 2026-05-17T02:18:52.525741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation f513ac82-3afd-443b-9b98-0c27709462b8 · outbound

This paper cites 19 B.2 Details of Selective Slot Activation.

Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis 19 B.2 Details of Selective Slot Activation

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 1773eb7d-8f4f-49af-bf28-4c820bd105f9 · outbound

This paper cites (8) B.2 DETAILS OFSELECTIVESLOTACTIVATION To achieve sparse yet differentiable slot selection, we adopt the Gumbel-Top-K(Gumbel, 1954; Maddison et al., 2014; Kool et al.

Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis (8) B.2 DETAILS OFSELECTIVESLOTACTIVATION To achieve sparse yet differentiable slot selection, we adopt the Gumbel-Top-K(Gumbel, 1954; Maddison et al., 2014; Kool et al

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation cffd7e24-2017-4d7a-8983-b2684f179ea1 · outbound

This paper cites Given slot scoresr∈R S, we add i.i.d.

Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis Given slot scoresr∈R S, we add i.i.d

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation c240d5d9-17c0-43cf-931f-7a34619b9491 · outbound

This paper cites For genomics, slot embeddingsS g are decoded to approximate the original pathway embeddingsX g, guided by the positional embeddings Qg (Eq.

Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis For genomics, slot embeddingsS g are decoded to approximate the original pathway embeddingsX g, guided by the positional embeddings Qg (Eq

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 9bc35a13-ec64-415d-b8dd-2162398f63f7 · outbound

This paper cites Histological data include all diagnostic WSIs, while transcriptomic profiles with DSS labels are obtained from cBioPortal.

Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis Histological data include all diagnostic WSIs, while transcriptomic profiles with DSS labels are obtained from cBioPortal

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 85f5555c-28c9-4246-9577-8b8fb1670393 · outbound

This paper cites an unresolved cited work.

Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis Unresolved cited work

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 1573c1be-527d-4f53-afbd-5757bac4900f · outbound

This paper cites Evaluation.

Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis Evaluation

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation cad01a81-0f58-49b7-bbf5-f81f7c841429 · outbound

This paper cites In addition, we compute the restricted mean survival time (RMST) (Irwin, 1949; Karrison, 1986).

Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis In addition, we compute the restricted mean survival time (RMST) (Irwin, 1949; Karrison, 1986)

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation c20f8f3f-b6f9-4649-88b7-e7ccadb82397 · outbound

This paper cites an unresolved cited work.

Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis Unresolved cited work

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation f5248c9c-6283-4b6c-b8aa-e99200df8def · outbound

This paper cites For completeness, we also include two strong methods (MOTCAT and CMTA).

Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis For completeness, we also include two strong methods (MOTCAT and CMTA)

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation c7219648-d345-42fc-9623-e1c6302b3a49 · outbound

This paper cites an unresolved cited work.

Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis Unresolved cited work

Reference 22

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unresolved
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation ef691ce8-efb9-47aa-8c8a-1f44b68af8bd · outbound

This paper cites This setting tests whether SlotSPE 25 Table 8: Ablation of model components reported as C-index (mean±std) across ten cancer datasets.

Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis This setting tests whether SlotSPE 25 Table 8: Ablation of model components reported as C-index (mean±std) across ten cancer datasets

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation dd554683-ca5a-4817-86aa-87641c6686dc · outbound

This paper cites an unresolved cited work.

Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis Unresolved cited work

Reference 24

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 93d548b4-c300-49eb-923a-19ce82ac014c · outbound

This paper cites LD-CV AE attains the second-best performance, yet its reliance on a variational autoencoder introduces sub- stantial memory and runtime overhead.

Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis LD-CV AE attains the second-best performance, yet its reliance on a variational autoencoder introduces sub- stantial memory and runtime overhead

Reference 25

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation b98244be-b47d-4eea-ac48-5fc732d73ec5 · outbound

This paper cites treat-all.

Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis treat-all

Reference 26

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raw_fallback, observed 2026-05-17T02:18:53.114574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Pith citing papers

No inbound Pith citation observations are available.