Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-17T02:17:15.595874Z
Paper Citation Record · LEDGER
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.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-17T02:17:15.595874Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
26 of 26 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation e9a77c0a-7848-4f47-93a1-1d7709c8c53e · outbound
Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis Deep Variational Information Bottleneck
Reference 1
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.
Observation 91008d40-ed90-4acf-8e56-3999502da03f · outbound
Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis The reactome pathway knowledgebase 2022.Nucleic acids research, 50(D1):D687–D692
Reference 2
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.
Observation 1039267a-fc1c-459c-9b2d-8ce685f1be25 · outbound
Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis On the Binding Problem in Artificial Neural Networks
Reference 3
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.
Observation 4cce8392-d272-4f5e-82f1-e690780f897b · outbound
Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis Categorical Reparameterization with Gumbel-Softmax
Reference 4
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.
Observation ae1cc5e1-9de9-452c-9069-e0b22c34195c · outbound
Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis Adam: A Method for Stochastic Optimization
Reference 5
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.
Observation fe8a11dd-8157-46be-98c8-651a3f4baacd · outbound
Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis Adaptive Prototype Learning for Multimodal Cancer Survival Analysis
Reference 6
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.
Observation cedbeb5d-9bb0-405e-82d6-593ae920aab9 · outbound
Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis Multimodal Prototyping for cancer survival prediction
Reference 7
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.
Observation 5f15b631-fbe6-4cb8-a910-09868ca86490 · outbound
Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis The information bottleneck method
Reference 8
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.
Observation 7c8f79fc-b700-4cca-8191-2028aa0a0845 · outbound
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
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.
Observation dad6812b-d42a-4af4-9f42-339a3dd358b2 · outbound
Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis AdaMHF: Adaptive Multimodal Hierarchical Fusion for Survival Prediction
Reference 10
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.
Observation 276e5fe9-7ff2-4ce8-8fd6-45a35541de2b · outbound
Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis Prototypical Information Bottlenecking and Disentangling for Multimodal Cancer Survival Prediction
Reference 11
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.
Observation f513ac82-3afd-443b-9b98-0c27709462b8 · outbound
Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis 19 B.2 Details of Selective Slot Activation
Reference 12
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.
Observation 1773eb7d-8f4f-49af-bf28-4c820bd105f9 · outbound
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
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.
Observation cffd7e24-2017-4d7a-8983-b2684f179ea1 · outbound
Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis Given slot scoresr∈R S, we add i.i.d
Reference 14
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.
Observation c240d5d9-17c0-43cf-931f-7a34619b9491 · outbound
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
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.
Observation 9bc35a13-ec64-415d-b8dd-2162398f63f7 · outbound
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
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.
Observation 85f5555c-28c9-4246-9577-8b8fb1670393 · outbound
Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis Unresolved cited work
Reference 17
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.
Observation 1573c1be-527d-4f53-afbd-5757bac4900f · outbound
Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis Evaluation
Reference 18
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.
Observation cad01a81-0f58-49b7-bbf5-f81f7c841429 · outbound
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
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.
Observation c20f8f3f-b6f9-4649-88b7-e7ccadb82397 · outbound
Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis Unresolved cited work
Reference 20
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.
Observation f5248c9c-6283-4b6c-b8aa-e99200df8def · outbound
Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis For completeness, we also include two strong methods (MOTCAT and CMTA)
Reference 21
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.
Observation c7219648-d345-42fc-9623-e1c6302b3a49 · outbound
Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis Unresolved cited work
Reference 22
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.
Observation ef691ce8-efb9-47aa-8c8a-1f44b68af8bd · outbound
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
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.
Observation dd554683-ca5a-4817-86aa-87641c6686dc · outbound
Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis Unresolved cited work
Reference 24
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.
Observation 93d548b4-c300-49eb-923a-19ce82ac014c · outbound
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
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.
Observation b98244be-b47d-4eea-ac48-5fc732d73ec5 · outbound
Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis treat-all
Reference 26
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.
No inbound Pith citation observations are available.