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Paper Citation Record · LEDGER

Rad-JEPA 3D: Radiology Joint-Embedding Predictive Model for 3D Computed Tomography

As of 15 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:2607.26196.

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

pith.paper-citation-record.v1
2607.26196 v1

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T00:38:27.205080Z

measured 20 of 20 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

20 of 20 outbound references displayed

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External citation measurements

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Outbound references

Observation 22b160d3-ff99-4bcc-8019-b083cedd31fd · outbound

This paper cites Gqa: Training generalized multi-query transformer models from multi-head checkpoints.

Rad-JEPA 3D: Radiology Joint-Embedding Predictive Model for 3D Computed Tomography Gqa: Training generalized multi-query transformer models from multi-head checkpoints

Reference 1

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source=pdf_text observed=2026-08-01T00:38:25.770734Z digest=sha256:1d4c72e7639e1c779a532d20b269ea937d8aa11d700cc1634ca84cc92d8142f8

Observation 3629b68a-4603-4fe1-8f3b-a87ebbd4923a · outbound

This paper cites Masked and Predictive Self-Supervised Foundation Models for 3D Brain MRI.

Rad-JEPA 3D: Radiology Joint-Embedding Predictive Model for 3D Computed Tomography Masked and Predictive Self-Supervised Foundation Models for 3D Brain MRI

Reference 5

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source=pdf_text observed=2026-08-01T00:38:26.092799Z digest=sha256:1a85158c29dcb51ca63495f72deeade91bf1e971dff7f6dbb242ff55053bc090

Observation f479b64a-f925-4b5e-95c5-e3bf5b94d208 · outbound

This paper cites Li, Aravind R.

Rad-JEPA 3D: Radiology Joint-Embedding Predictive Model for 3D Computed Tomography Li, Aravind R

Reference 6

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source=pdf_text observed=2026-08-01T00:38:26.161401Z digest=sha256:2fc00204a3eee86908b0c9e262c072242dbe7154ab0185737432fd5e753a2361

Observation 08602dc4-92a1-432a-bba0-51a987d62e85 · outbound

This paper cites Decoupled Weight Decay Regularization.

Rad-JEPA 3D: Radiology Joint-Embedding Predictive Model for 3D Computed Tomography Decoupled Weight Decay Regularization

Reference 8

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source=pdf_text observed=2026-08-01T00:38:26.331911Z digest=sha256:3f44c86a4e71b0bacac1c66ce251b829693b141e4413d566162c7d830d0da223

Observation 4de1f005-3e32-417e-910d-0d11d4c09e1a · outbound

This paper cites V-JEPA 2.1: Unlocking Dense Features in Video Self-Supervised Learning.

Rad-JEPA 3D: Radiology Joint-Embedding Predictive Model for 3D Computed Tomography V-JEPA 2.1: Unlocking Dense Features in Video Self-Supervised Learning

Reference 11

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source=pdf_text observed=2026-08-01T00:38:26.561459Z digest=sha256:70e0149134ef89b6341dbbba68c90730b92923dadd41b3f189b2566197892cb1

Observation 6cbd6758-fb13-4717-a0a1-c0e98505b618 · outbound

This paper cites UniMedVL: Unifying Medical Multimodal Understanding and Generation through Observation-Knowledge-Analysis.

Rad-JEPA 3D: Radiology Joint-Embedding Predictive Model for 3D Computed Tomography UniMedVL: Unifying Medical Multimodal Understanding and Generation through Observation-Knowledge-Analysis

Reference 12

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source=pdf_text observed=2026-08-01T00:38:26.614608Z digest=sha256:74161f31cb7f4b9b369ea1a65b59bd2886eafa771394f6fc6551290ee245ab5c

Observation e7c890f4-09b1-4966-b476-37a81410d9d2 · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

Rad-JEPA 3D: Radiology Joint-Embedding Predictive Model for 3D Computed Tomography DINOv2: Learning Robust Visual Features without Supervision

Reference 13

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source=pdf_text observed=2026-08-01T00:38:26.683807Z digest=sha256:347244e3966690ed97b7172809839a51f8972890e0e76ea325cbb6ba2d9a0854

Observation ee444b32-ebe8-4741-a5d5-7a46070674e0 · outbound

This paper cites Arnold, and William Speier.

Rad-JEPA 3D: Radiology Joint-Embedding Predictive Model for 3D Computed Tomography Arnold, and William Speier

Reference 14

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source=pdf_text observed=2026-08-01T00:38:26.765295Z digest=sha256:1fafbb4f92828cd777a2f97e9cc4631b066b91f58ee120a3b3d32508567e1152

Observation b5d0e467-933d-40e1-9b5e-76276c821962 · outbound

This paper cites DINOv3.

Rad-JEPA 3D: Radiology Joint-Embedding Predictive Model for 3D Computed Tomography DINOv3

Reference 15

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source=pdf_text observed=2026-08-01T00:38:26.845070Z digest=sha256:9ba1f2844b6c3677b70f10b83e0109115e1a08c100b284a2469f7a4bcca95c27

Observation 586d604d-cea0-4b85-9dab-430f9e9095dc · outbound

This paper cites Virchow: A Million-Slide Digital Pathology Foundation Model.

Rad-JEPA 3D: Radiology Joint-Embedding Predictive Model for 3D Computed Tomography Virchow: A Million-Slide Digital Pathology Foundation Model

Reference 17

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source=pdf_text observed=2026-08-01T00:38:26.969909Z digest=sha256:b3ab2f2a3c99fa4d6863c7b071a2e993275d24bdc71ce42801519510c11929db

Observation 3ab04933-22f3-4cd4-9ada-82d85d8031be · outbound

This paper cites Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution.

Rad-JEPA 3D: Radiology Joint-Embedding Predictive Model for 3D Computed Tomography Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 18

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source=pdf_text observed=2026-08-01T00:38:27.036934Z digest=sha256:27a6934a02086790625854a1f1389f8249a7fee58ac98349fd90edc1e74557d7

Observation 3d210b6c-45ca-4a18-99f4-61b72b4fe354 · outbound

This paper cites Jure Zbontar, Li Jing, Ishan Misra, Yann LeCun, and St´ephane Deny.

Rad-JEPA 3D: Radiology Joint-Embedding Predictive Model for 3D Computed Tomography Jure Zbontar, Li Jing, Ishan Misra, Yann LeCun, and St´ephane Deny

Reference 19

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source=pdf_text observed=2026-08-01T00:38:27.136877Z digest=sha256:80419d46e8bd7154e7bfe709678a0e933f55a9fbb0c58a419f2957845f620f20

Observation 9711f7ee-6e67-4df9-80e8-40d8788d566f · outbound

This paper cites Gotway, and Jianming Liang.

Rad-JEPA 3D: Radiology Joint-Embedding Predictive Model for 3D Computed Tomography Gotway, and Jianming Liang

Reference 20

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source=pdf_text observed=2026-08-01T00:38:27.205080Z digest=sha256:f2d2c5b23877bd4cf772bc614c19f3b2bf37fca09e3394cdeba0d712c59a682f

Observation 3660fe2c-6f39-43cd-8d0d-2cd01756be6a · outbound

This paper cites VolTA-3D: Self-Supervised Learning for Brain MRI using 3D Volumetric Token Alignment.

Rad-JEPA 3D: Radiology Joint-Embedding Predictive Model for 3D Computed Tomography VolTA-3D: Self-Supervised Learning for Brain MRI using 3D Volumetric Token Alignment

Reference 2017

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source=pdf_text observed=2026-08-01T00:38:26.402664Z digest=sha256:4406844bf9f9784cd800af32d1861ae06fe56343f824f6bfdbb4e898fef7b8e9

Observation c0c13d68-673d-4e3d-8620-2bbc419e8d3d · outbound

This paper cites M3D: Advancing 3D Medical Image Analysis with Multi-Modal Large Language Models.

Rad-JEPA 3D: Radiology Joint-Embedding Predictive Model for 3D Computed Tomography M3D: Advancing 3D Medical Image Analysis with Multi-Modal Large Language Models

Reference 2021

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source=pdf_text observed=2026-08-01T00:38:25.843369Z digest=sha256:94ff760f64c74bf121b52a5b508f92a364f56161c8278892fda40fe2925d08c5

Observation bd428541-2b5b-49af-8af2-ac17ec3a2430 · outbound

This paper cites Beyond Medical Diagnostics: How Medical Multimodal Large Language Models Think in Space.

Rad-JEPA 3D: Radiology Joint-Embedding Predictive Model for 3D Computed Tomography Beyond Medical Diagnostics: How Medical Multimodal Large Language Models Think in Space

Reference 2022

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source=pdf_text observed=2026-08-01T00:38:26.906488Z digest=sha256:541659cc6d72b19905f0a9d8474abad5f60c1fecca882a45fee8ab71f0a819bb

Observation 54a568ed-1bf0-4268-b853-ac9cb0fa00f5 · outbound

This paper cites V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning.

Rad-JEPA 3D: Radiology Joint-Embedding Predictive Model for 3D Computed Tomography V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning

Reference 2023

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source=pdf_text observed=2026-08-01T00:38:25.818751Z digest=sha256:0e9a26d81ea97346fffd36cbe360de2db04fbd05e49830ce8919af10523aa469

Observation 8b220415-dab6-4638-a79d-7d8b53285a55 · outbound

This paper cites Revisiting Feature Prediction for Learning Visual Representations from Video.

Rad-JEPA 3D: Radiology Joint-Embedding Predictive Model for 3D Computed Tomography Revisiting Feature Prediction for Learning Visual Representations from Video

Reference 2024

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source=pdf_text observed=2026-08-01T00:38:25.974820Z digest=sha256:e780308a5fad7169e88d271ecdea521ccae9b2b5c3634fae149a092c3d5792be

Observation 5a7c62c7-d235-4cac-aa6d-b5a4b9193e54 · outbound

This paper cites HealthGPT: A Medical Large Vision-Language Model for Unifying Comprehension and Generation via Heterogeneous Knowledge Adaptation.

Rad-JEPA 3D: Radiology Joint-Embedding Predictive Model for 3D Computed Tomography HealthGPT: A Medical Large Vision-Language Model for Unifying Comprehension and Generation via Heterogeneous Knowledge Adaptation

Reference 2025

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source=pdf_text observed=2026-08-01T00:38:26.226015Z digest=sha256:1048a025aed1d0989e491d95d7d250d2baec2b32a064a50e429d9f7f2528bd38

Observation 731d6474-ec27-4be8-b630-91e848c08512 · outbound

This paper cites Lost in Volume: The CT-SpatialVQA Benchmark for Evaluating Semantic-Spatial Understanding of 3D Medical Vision-Language Models.

Rad-JEPA 3D: Radiology Joint-Embedding Predictive Model for 3D Computed Tomography Lost in Volume: The CT-SpatialVQA Benchmark for Evaluating Semantic-Spatial Understanding of 3D Medical Vision-Language Models

Reference 2026

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source=pdf_text observed=2026-08-01T00:38:26.497823Z digest=sha256:599403ebf195c5013acc733dc7b8b86e4b9107cbda3509bc2dbc55a73e345855

Pith citing papers

No inbound Pith citation observations are available.