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Paper Citation Record · LEDGER

Adversarial Learning for Neural PDE Solvers with Sparse Data

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2409.02431.

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

pith.paper-citation-record.v1
2409.02431 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:31:05.803294Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T17:00:03.388696Z

Reference resolution

0 of 0 outbound references displayed

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  • verified fuzzy0
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  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 2d4c059e-8262-4ee5-858c-6ec177edf7cf · inbound

Fusing Physics-Driven Strategies and Cross-Modal Adversarial Learning: Toward Multi-Domain Applications cites this paper.

Fusing Physics-Driven Strategies and Cross-Modal Adversarial Learning: Toward Multi-Domain Applications Adversarial Learning for Neural PDE Solvers with Sparse Data

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-12T05:31:24.174152Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T05:31:24.174152Z digest=sha256:f582d64acfdbec39f784a50a51d5ede3dfeeaf26639c5d0880d1006de3c36eef

Observation b0baae3c-b049-4cd6-ac8f-f21f3d3f1ce2 · inbound

On the Mechanisms of Adversarial Data Augmentation for Robust and Adaptive Transfer Learning cites this paper.

On the Mechanisms of Adversarial Data Augmentation for Robust and Adaptive Transfer Learning Adversarial Learning for Neural PDE Solvers with Sparse Data

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-15T20:31:05.803294Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:31:05.803294Z digest=sha256:aa147746c1c438e0cb2232e48d02172862fa23e73d445a56771835efb5802e34

Observation 1b5a46c7-aa8e-4009-9b90-615643537c12 · inbound

GAMA: Geometry-Aware Manifold Alignment via Structured Adversarial Perturbations for Robust Domain Adaptation cites this paper.

GAMA: Geometry-Aware Manifold Alignment via Structured Adversarial Perturbations for Robust Domain Adaptation Adversarial Learning for Neural PDE Solvers with Sparse Data

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T15:26:10.751436Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:26:10.751436Z digest=sha256:c3c0910a64a7bd1b78a6ee2ec8fd8f155f00afc66ed33c7510c4ad73f8590c15

Observation 6079d342-f93b-4f91-92a1-61c2daa5b5fd · inbound

Dynamic Modality Scheduling for Multimodal Large Models via Confidence, Uncertainty, and Semantic Consistency cites this paper.

Dynamic Modality Scheduling for Multimodal Large Models via Confidence, Uncertainty, and Semantic Consistency Adversarial Learning for Neural PDE Solvers with Sparse Data

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-07T00:47:50.370161Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:47:50.370161Z digest=sha256:ac5e96466e8ba8ed5b511e235a1b89e3cec33752c17e238f91ea6caf321f0a8b

Observation 3bcd8310-5726-4b88-a7b0-9f0ad4c3b511 · inbound

FADE: Adversarial Concept Erasure in Flow Models cites this paper.

FADE: Adversarial Concept Erasure in Flow Models Adversarial Learning for Neural PDE Solvers with Sparse Data

Reference 2022

Resolution
verified exact
local_arxiv, observed 2026-08-06T17:00:03.427058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T17:00:00.481391Z digest=sha256:c05dc51d0ce1964fe70164cbaeb35cb6f44188e0f2e7291b7a702cb9a74ef693