Paper Citation Record · LEDGER

Raptor: Scalable Train-Free Embeddings for 3D Medical Volumes Leveraging Pretrained 2D Foundation Models

As of 18 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 4 inbound Pith citation observations for arXiv:2507.08254.

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

pith.paper-citation-record.v1
2507.08254 v1

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:29:09.047332Z

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T22:59:23.923891Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T12:08:15.488526Z

Reference resolution

13 of 13 outbound references displayed

verified exact0
verified fuzzy3
unresolved10
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3bdf0336-6265-49e0-b9ba-3bea0243ce44 · outbound

This paper cites Ebrahimi, A., Luo, S., and Chiong, R.

Raptor: Scalable Train-Free Embeddings for 3D Medical Volumes Leveraging Pretrained 2D Foundation Models Ebrahimi, A., Luo, S., and Chiong, R

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:29:10.312930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 540653e1-7103-4555-8722-48acddeca9e6 · outbound

This paper cites LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One Day.

Raptor: Scalable Train-Free Embeddings for 3D Medical Volumes Leveraging Pretrained 2D Foundation Models LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One Day

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T18:29:08.148139Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0dbfb80b-81b7-4991-b20b-6e492b3756c4 · outbound

This paper cites OCTCube-M: A 3D multimodal optical coherence tomography foundation model for retinal and systemic diseases with cross-cohort and cross-device validation.

Raptor: Scalable Train-Free Embeddings for 3D Medical Volumes Leveraging Pretrained 2D Foundation Models OCTCube-M: A 3D multimodal optical coherence tomography foundation model for retinal and systemic diseases with cross-cohort and cross-device validation

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T18:29:08.247025Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3b8dc2dc-e89e-4ad8-ab03-42bb224ad05c · outbound

This paper cites V-net: Fully con- volutional neural networks for volumetric medical image segmentation.

Raptor: Scalable Train-Free Embeddings for 3D Medical Volumes Leveraging Pretrained 2D Foundation Models V-net: Fully con- volutional neural networks for volumetric medical image segmentation

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:29:09.798477Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ba5c6693-0eef-47de-9367-5a32b566bb7e · outbound

This paper cites Med-Flamingo: a Multimodal Medical Few-shot Learner.

Raptor: Scalable Train-Free Embeddings for 3D Medical Volumes Leveraging Pretrained 2D Foundation Models Med-Flamingo: a Multimodal Medical Few-shot Learner

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T18:29:08.471062Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation efaa67a8-eef6-4d53-a52d-f3d9bf2efef7 · outbound

This paper cites Large-Scale 3D Medical Image Pre-training with Geometric Context Priors.

Raptor: Scalable Train-Free Embeddings for 3D Medical Volumes Leveraging Pretrained 2D Foundation Models Large-Scale 3D Medical Image Pre-training with Geometric Context Priors

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T18:29:08.886873Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d72364e-6c5e-4958-a447-0d6984493e16 · outbound

This paper cites Appendix A.1.

Raptor: Scalable Train-Free Embeddings for 3D Medical Volumes Leveraging Pretrained 2D Foundation Models Appendix A.1

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:29:09.553441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9a7ab5f1-236f-4581-8bb8-648bbe61df19 · outbound

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

Raptor: Scalable Train-Free Embeddings for 3D Medical Volumes Leveraging Pretrained 2D Foundation Models DINOv2: Learning Robust Visual Features without Supervision

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-06T18:29:08.624252Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ce6bad37-068d-4058-a7c9-6f2c1178e625 · outbound

This paper cites an unresolved cited work.

Raptor: Scalable Train-Free Embeddings for 3D Medical Volumes Leveraging Pretrained 2D Foundation Models Unresolved cited work

Reference 2020

Resolution: unresolved; raw_fallback, observed 2026-08-06T18:29:10.088887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation be86fea0-2640-411d-8831-1d4da1b771e8 · outbound

This paper cites ShapeNet: An Information-Rich 3D Model Repository.

Raptor: Scalable Train-Free Embeddings for 3D Medical Volumes Leveraging Pretrained 2D Foundation Models ShapeNet: An Information-Rich 3D Model Repository

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-06T18:29:07.663309Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 98c458b1-90e9-4f00-be54-61bde74c2cbc · outbound

This paper cites MIS-FM: 3D Medical Image Segmentation using Foundation Models Pretrained on a Large-Scale Unannotated Dataset.

Raptor: Scalable Train-Free Embeddings for 3D Medical Volumes Leveraging Pretrained 2D Foundation Models MIS-FM: 3D Medical Image Segmentation using Foundation Models Pretrained on a Large-Scale Unannotated Dataset

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-06T18:29:08.761161Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dbe58d09-2280-4cd4-9efb-83fcd2722b81 · outbound

This paper cites E3D-GPT: Enhanced 3D Visual Foundation for Medical Vision-Language Model.

Raptor: Scalable Train-Free Embeddings for 3D Medical Volumes Leveraging Pretrained 2D Foundation Models E3D-GPT: Enhanced 3D Visual Foundation for Medical Vision-Language Model

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-06T18:29:07.989205Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8a9d2002-a84d-411f-a13d-6e13e762d087 · outbound

This paper cites an unresolved cited work.

Raptor: Scalable Train-Free Embeddings for 3D Medical Volumes Leveraging Pretrained 2D Foundation Models Unresolved cited work

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-06T18:29:07.575375Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation bea0e375-5c01-4798-8c99-b2c678e82931 · inbound

Training-Free Zero-Shot Anomaly Detection in 3D Brain MRI with 2D Foundation Models cites this paper.

Training-Free Zero-Shot Anomaly Detection in 3D Brain MRI with 2D Foundation Models Raptor: Scalable Train-Free Embeddings for 3D Medical Volumes Leveraging Pretrained 2D Foundation Models

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-02T22:59:23.923891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bfb48228-85c2-499f-9c7f-ca3d7fa2d06d · inbound

WISTERIA: Learning Clinical Representations from Noisy Supervision via Multi-View Consistency in Electronic Health Records cites this paper.

WISTERIA: Learning Clinical Representations from Noisy Supervision via Multi-View Consistency in Electronic Health Records Raptor: Scalable Train-Free Embeddings for 3D Medical Volumes Leveraging Pretrained 2D Foundation Models

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-12T07:41:45.109193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 70dadd68-bd8e-4d49-a2fa-e4485e368ea8 · inbound

AURORA: Contextual Orthogonalization for Geometric Representation Learning in Healthcare Foundation Models cites this paper.

AURORA: Contextual Orthogonalization for Geometric Representation Learning in Healthcare Foundation Models Raptor: Scalable Train-Free Embeddings for 3D Medical Volumes Leveraging Pretrained 2D Foundation Models

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-20T12:08:15.490400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 387001ff-eccc-4a0e-bbd8-b128fea6e4ba · inbound

MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms cites this paper.

MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Raptor: Scalable Train-Free Embeddings for 3D Medical Volumes Leveraging Pretrained 2D Foundation Models

Reference 30

Resolution: unresolved; no resolver link, observed 2026-07-14T16:31:09.661787Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.