Paper Citation Record · LEDGER

Cross-Modal Fine-Tuning of 3D Convolutional Foundation Models for ADHD Classification with Low-Rank Adaptation

As of 11 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 1 inbound Pith citation observation for arXiv:2511.06163.

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

pith.paper-citation-record.v1
2511.06163 v2

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T23:23:15.710196Z

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T23:23:13.363824Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

25 of 25 outbound references displayed

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unresolved25
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External citation measurements

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Outbound references

Observation e784a291-f786-4a98-a4e8-d9bb406fbb3c · outbound

This paper cites Early diag- nosis is crucial for improving educational, social, and mental health outcomes [2].

Cross-Modal Fine-Tuning of 3D Convolutional Foundation Models for ADHD Classification with Low-Rank Adaptation Early diag- nosis is crucial for improving educational, social, and mental health outcomes [2]

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-03T23:23:13.322214Z

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Observation a7a263b9-8768-4edd-bb23-f0693d90bce5 · outbound

This paper cites Foundation Model Fig.

Cross-Modal Fine-Tuning of 3D Convolutional Foundation Models for ADHD Classification with Low-Rank Adaptation Foundation Model Fig

Reference 2

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Observation 84928ff3-3739-4d79-ba4e-26b2212e958d · outbound

This paper cites Emotion and Devel- opment Branch Phenotyping and DTI.

Cross-Modal Fine-Tuning of 3D Convolutional Foundation Models for ADHD Classification with Low-Rank Adaptation Emotion and Devel- opment Branch Phenotyping and DTI

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-03T23:23:13.534287Z

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Observation bbfbbf0d-cd08-42e2-b4fe-3acc0b1f3ddb · outbound

This paper cites an unresolved cited work.

Cross-Modal Fine-Tuning of 3D Convolutional Foundation Models for ADHD Classification with Low-Rank Adaptation Unresolved cited work

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-03T23:23:13.612507Z

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Observation 824cfe22-b27d-4f6c-9063-5d9cbda2ee9a · outbound

This paper cites This cross-modal adaptation achieved new state-of-the-art results for ADHD diagnosis using only two diffusion MRI-derived feature maps, including FA and MD, as input.

Cross-Modal Fine-Tuning of 3D Convolutional Foundation Models for ADHD Classification with Low-Rank Adaptation This cross-modal adaptation achieved new state-of-the-art results for ADHD diagnosis using only two diffusion MRI-derived feature maps, including FA and MD, as input

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-03T23:23:13.683284Z

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Observation c81e29cf-b6a8-4824-8054-a7565fef35d8 · outbound

This paper cites Cross-Modal Fine-Tuning of 3D Convolutional Foundation Models for ADHD Classification with Low-Rank Adaptation.

Cross-Modal Fine-Tuning of 3D Convolutional Foundation Models for ADHD Classification with Low-Rank Adaptation Cross-Modal Fine-Tuning of 3D Convolutional Foundation Models for ADHD Classification with Low-Rank Adaptation

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-03T23:23:13.363824Z

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Observation 187c2184-5ecd-41ee-bd7e-d494e04ffc90 · outbound

This paper cites an unresolved cited work.

Cross-Modal Fine-Tuning of 3D Convolutional Foundation Models for ADHD Classification with Low-Rank Adaptation Unresolved cited work

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-03T23:23:13.794465Z

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Observation 41e8d04a-7a5e-407e-8916-f18b89983b63 · outbound

This paper cites Xiaofeng Liu for insightful discus- sions.

Cross-Modal Fine-Tuning of 3D Convolutional Foundation Models for ADHD Classification with Low-Rank Adaptation Xiaofeng Liu for insightful discus- sions

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-03T23:23:13.880424Z

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Observation 7e64b276-33e2-4e2b-adba-3ca635bcea6e · outbound

This paper cites New insights into attention-deficit/hyperactivity disorder using structural neuroimaging,.

Cross-Modal Fine-Tuning of 3D Convolutional Foundation Models for ADHD Classification with Low-Rank Adaptation New insights into attention-deficit/hyperactivity disorder using structural neuroimaging,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-03T23:23:13.977499Z

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Observation 26126819-8553-4907-9901-467844e921ff · outbound

This paper cites Why the diagnosis of attention deficit hyperactivity dis- order matters,.

Cross-Modal Fine-Tuning of 3D Convolutional Foundation Models for ADHD Classification with Low-Rank Adaptation Why the diagnosis of attention deficit hyperactivity dis- order matters,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-03T23:23:14.049644Z

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Observation a2a665e5-8a6e-451b-878a-cebe476cb731 · outbound

This paper cites Multimodal mr images-based diagnosis of early adolescent attention- deficit/hyperactivity disorder using multiple kernel learning,.

Cross-Modal Fine-Tuning of 3D Convolutional Foundation Models for ADHD Classification with Low-Rank Adaptation Multimodal mr images-based diagnosis of early adolescent attention- deficit/hyperactivity disorder using multiple kernel learning,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-03T23:23:14.136537Z

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Observation 2a36d706-df86-4378-a61b-c6870728fcf3 · outbound

This paper cites Population level multimodal neu- roimaging correlates of attention-deficit hyperactivity disorder among children,.

Cross-Modal Fine-Tuning of 3D Convolutional Foundation Models for ADHD Classification with Low-Rank Adaptation Population level multimodal neu- roimaging correlates of attention-deficit hyperactivity disorder among children,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T23:23:14.220683Z

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Observation 31be100c-945d-4ee9-9790-1dd4a69fe361 · outbound

This paper cites Machine-learning-based feature selection to identify attention-deficit hyperactivity disorder using whole- brain white matter microstructure: A longitudinal study,.

Cross-Modal Fine-Tuning of 3D Convolutional Foundation Models for ADHD Classification with Low-Rank Adaptation Machine-learning-based feature selection to identify attention-deficit hyperactivity disorder using whole- brain white matter microstructure: A longitudinal study,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-03T23:23:14.291138Z

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Observation 65b38c89-264c-406d-bb49-4155868e75fd · outbound

This paper cites Foundation model for cancer imaging biomarkers,.

Cross-Modal Fine-Tuning of 3D Convolutional Foundation Models for ADHD Classification with Low-Rank Adaptation Foundation model for cancer imaging biomarkers,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-03T23:23:14.295467Z

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Observation e984212b-42da-4d62-a411-085b37f8b0e4 · outbound

This paper cites Lora: Low-rank adaptation of large lan- guage models.,.

Cross-Modal Fine-Tuning of 3D Convolutional Foundation Models for ADHD Classification with Low-Rank Adaptation Lora: Low-rank adaptation of large lan- guage models.,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-03T23:23:14.473166Z

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Observation 2e397c07-53f9-4665-9455-b3ba37b57d0d · outbound

This paper cites Customized Segment Anything Model for Medical Image Segmentation.

Cross-Modal Fine-Tuning of 3D Convolutional Foundation Models for ADHD Classification with Low-Rank Adaptation Customized Segment Anything Model for Medical Image Segmentation

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-03T23:23:14.605621Z

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Observation 0382a6bc-9aa3-4ddf-8566-327e4deefee0 · outbound

This paper cites Lora-enhanced rt- detr: First low-rank adaptation based detr for real-time full body anatomical structures identification in muscu- loskeletal ultrasound,.

Cross-Modal Fine-Tuning of 3D Convolutional Foundation Models for ADHD Classification with Low-Rank Adaptation Lora-enhanced rt- detr: First low-rank adaptation based detr for real-time full body anatomical structures identification in muscu- loskeletal ultrasound,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-03T23:23:14.719933Z

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Observation 50953679-a45c-4f4d-a5f6-151d82bef171 · outbound

This paper cites 3d u-net: learning dense volumetric segmentation from sparse annotation,.

Cross-Modal Fine-Tuning of 3D Convolutional Foundation Models for ADHD Classification with Low-Rank Adaptation 3d u-net: learning dense volumetric segmentation from sparse annotation,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-03T23:23:14.791917Z

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Observation fc4a3275-4b4b-4933-9c58-388f676f5ac1 · outbound

This paper cites Models genesis,.

Cross-Modal Fine-Tuning of 3D Convolutional Foundation Models for ADHD Classification with Low-Rank Adaptation Models genesis,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-03T23:23:14.927264Z

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Observation a87a1764-0e0d-4821-8c7c-5f2daa3d5379 · outbound

This paper cites Can spatiotemporal 3d cnns retrace the history of 2d cnns and imagenet?,.

Cross-Modal Fine-Tuning of 3D Convolutional Foundation Models for ADHD Classification with Low-Rank Adaptation Can spatiotemporal 3d cnns retrace the history of 2d cnns and imagenet?,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-03T23:23:15.100964Z

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Observation cd550e51-e136-4255-ba80-743463722de7 · outbound

This paper cites Med3D: Transfer Learning for 3D Medical Image Analysis.

Cross-Modal Fine-Tuning of 3D Convolutional Foundation Models for ADHD Classification with Low-Rank Adaptation Med3D: Transfer Learning for 3D Medical Image Analysis

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-03T23:23:15.223243Z

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Observation 0ee50d95-ae59-4c8a-b603-b16fbf20ca72 · outbound

This paper cites ”emotion and development branch phenotyping and dti (2012- 2017).

Cross-Modal Fine-Tuning of 3D Convolutional Foundation Models for ADHD Classification with Low-Rank Adaptation ”emotion and development branch phenotyping and dti (2012- 2017)

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-03T23:23:15.395030Z

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Observation 8302de07-944f-42f1-8bc9-cf4c0c55bfc3 · outbound

This paper cites Qsiprep: an integrative plat- form for preprocessing and reconstructing diffusion mri data,.

Cross-Modal Fine-Tuning of 3D Convolutional Foundation Models for ADHD Classification with Low-Rank Adaptation Qsiprep: an integrative plat- form for preprocessing and reconstructing diffusion mri data,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-03T23:23:15.506457Z

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Observation a825bd93-a16c-4dc1-a8c8-90ec9fca3661 · outbound

This paper cites An Inte- grated Approach to Correction for Off-Resonance Ef- fects and Subject Movement in Diffusion MR Imaging,.

Cross-Modal Fine-Tuning of 3D Convolutional Foundation Models for ADHD Classification with Low-Rank Adaptation An Inte- grated Approach to Correction for Off-Resonance Ef- fects and Subject Movement in Diffusion MR Imaging,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-03T23:23:15.586787Z

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Observation d14301ce-61a0-4a65-90ad-c9866623fdb4 · outbound

This paper cites A Reproducible Evaluation of ANTs Similarity Metric Performance in Brain Image Registration,.

Cross-Modal Fine-Tuning of 3D Convolutional Foundation Models for ADHD Classification with Low-Rank Adaptation A Reproducible Evaluation of ANTs Similarity Metric Performance in Brain Image Registration,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-03T23:23:15.710196Z

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Pith citing papers

Observation c81e29cf-b6a8-4824-8054-a7565fef35d8 · inbound