Paper Citation Record · LEDGER

Fusing Physics-Driven Strategies and Cross-Modal Adversarial Learning: Toward Multi-Domain Applications

As of 15 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2412.00341.

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

pith.paper-citation-record.v1
2412.00341 v1

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T05:31:24.246742Z

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+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

19 of 19 outbound references displayed

verified exact2
verified fuzzy12
unresolved5
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4ab960c0-f7d8-4b18-88a2-abe7fcc8fa35 · outbound

This paper cites Robust and data-efﬁcient generalization of self-supervised mach ine learning for diagnostic imaging.

Fusing Physics-Driven Strategies and Cross-Modal Adversarial Learning: Toward Multi-Domain Applications Robust and data-efﬁcient generalization of self-supervised mach ine learning for diagnostic imaging

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:31:24.577145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 6ef9adeb-4816-4af3-a706-5e35c48d7cd5 · outbound

This paper cites Managing ex- treme ai risks amid rapid progress.

Fusing Physics-Driven Strategies and Cross-Modal Adversarial Learning: Toward Multi-Domain Applications Managing ex- treme ai risks amid rapid progress

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:31:24.561982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 86e15c0e-c0d2-4276-a0cc-9c243ddec520 · outbound

This paper cites Cross-Modality Perturbation Synergy Attack for Person Re-identification.

Fusing Physics-Driven Strategies and Cross-Modal Adversarial Learning: Toward Multi-Domain Applications Cross-Modality Perturbation Synergy Attack for Person Re-identification

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-12T05:31:24.168379Z

Source-reported events for the cited work

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

This paper cites Adversarial Learning for Neural PDE Solvers with Sparse Data.

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

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Observation 5a5244fd-0ea4-497c-96bc-aa93543e9834 · outbound

This paper cites Beyond Augmentation: Empowering Model Robustness under Extreme Capture Environments.

Fusing Physics-Driven Strategies and Cross-Modal Adversarial Learning: Toward Multi-Domain Applications Beyond Augmentation: Empowering Model Robustness under Extreme Capture Environments

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-08-12T05:31:24.359289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a6e1923c-3e6e-4bbd-939c-58b9a960c87b · outbound

This paper cites Eliminate Deviation with Deviation for Data Augmentation and a General Multi-modal Data Learning Method.

Fusing Physics-Driven Strategies and Cross-Modal Adversarial Learning: Toward Multi-Domain Applications Eliminate Deviation with Deviation for Data Augmentation and a General Multi-modal Data Learning Method

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-12T05:31:24.184422Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aacd0e82-34e5-4e04-9c7c-3867b62a3506 · outbound

This paper cites Person re- identiﬁcation method based on color attack and joint de- fence.

Fusing Physics-Driven Strategies and Cross-Modal Adversarial Learning: Toward Multi-Domain Applications Person re- identiﬁcation method based on color attack and joint de- fence

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:31:24.546841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation fd0e262e-2d63-4649-8cf4-22db778159f1 · outbound

This paper cites Exploring Color Invariance through Image-Level Ensemble Learning.

Fusing Physics-Driven Strategies and Cross-Modal Adversarial Learning: Toward Multi-Domain Applications Exploring Color Invariance through Image-Level Ensemble Learning

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-12T05:31:24.194667Z

Source-reported events for the cited work

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Observation c615f80f-2ede-495f-82be-4a3bc638c4b6 · outbound

This paper cites An effective data aug- mentation for person re-identiﬁcation.

Fusing Physics-Driven Strategies and Cross-Modal Adversarial Learning: Toward Multi-Domain Applications An effective data aug- mentation for person re-identiﬁcation

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:31:24.531472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 099e7bf8-0182-4884-99af-86daf61b468d · outbound

This paper cites A Person Re-identification Data Augmentation Method with Adversarial Defense Effect.

Fusing Physics-Driven Strategies and Cross-Modal Adversarial Learning: Toward Multi-Domain Applications A Person Re-identification Data Augmentation Method with Adversarial Defense Effect

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-12T05:31:24.204217Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b004f80-59f6-4cd7-8a15-69aafb05a61a · outbound

This paper cites Person re-identiﬁcation method based on grayscale feature enhanc e- ment.

Fusing Physics-Driven Strategies and Cross-Modal Adversarial Learning: Toward Multi-Domain Applications Person re-identiﬁcation method based on grayscale feature enhanc e- ment

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:31:24.515289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 805bed76-1a56-47b8-8081-47472a60be8f · outbound

This paper cites Beyond Dropout: Robust Convolutional Neural Networks Based on Local Feature Masking.

Fusing Physics-Driven Strategies and Cross-Modal Adversarial Learning: Toward Multi-Domain Applications Beyond Dropout: Robust Convolutional Neural Networks Based on Local Feature Masking

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-08-12T05:31:24.290621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 03b05528-89e6-448e-a3df-32206dd23538 · outbound

This paper cites Learning mult iple layers of features from tiny images.

Fusing Physics-Driven Strategies and Cross-Modal Adversarial Learning: Toward Multi-Domain Applications Learning mult iple layers of features from tiny images

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:31:24.500119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f55091aa-dad4-4586-b371-1ebb1464811d · outbound

This paper cites Imagenet classiﬁcation with deep convolutional neural net - works.

Fusing Physics-Driven Strategies and Cross-Modal Adversarial Learning: Toward Multi-Domain Applications Imagenet classiﬁcation with deep convolutional neural net - works

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:31:24.484584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 360d0a3a-a1bf-458a-8246-55e5efeef14e · outbound

This paper cites Deep learning.

Fusing Physics-Driven Strategies and Cross-Modal Adversarial Learning: Toward Multi-Domain Applications Deep learning

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:31:24.467987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 45220fd5-fe9f-4783-b4e2-43b2ca3f4f0a · outbound

This paper cites Learning internal representations by error prop - agation, parallel distributed processing, explorations i n the microstructure of cognition, ed.

Fusing Physics-Driven Strategies and Cross-Modal Adversarial Learning: Toward Multi-Domain Applications Learning internal representations by error prop - agation, parallel distributed processing, explorations i n the microstructure of cognition, ed

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:31:24.452762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1a51155a-207a-4460-8fe6-77d60dda2082 · outbound

This paper cites Dropout: a simple way to prevent neural networks from overﬁtting.

Fusing Physics-Driven Strategies and Cross-Modal Adversarial Learning: Toward Multi-Domain Applications Dropout: a simple way to prevent neural networks from overﬁtting

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:31:24.437144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c8949450-bfa0-4def-b4a5-53b85f1f1a3c · outbound

This paper cites Visualiz- ing data using t-sne.

Fusing Physics-Driven Strategies and Cross-Modal Adversarial Learning: Toward Multi-Domain Applications Visualiz- ing data using t-sne

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:31:24.421563Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 91c7921a-1a28-4867-a835-8cc06d7ada72 · outbound

This paper cites Cross-modality perturbation syn- ergy attack for person re-identiﬁcation.

Fusing Physics-Driven Strategies and Cross-Modal Adversarial Learning: Toward Multi-Domain Applications Cross-modality perturbation syn- ergy attack for person re-identiﬁcation

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:31:24.406590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Pith citing papers

No inbound Pith citation observations are available.