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Paper Citation Record · LEDGER

MedTrinity-25M: A Large-scale Multimodal Dataset with Multigranular Annotations for Medicine

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 inbound Pith citation observations for arXiv:2408.02900.

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

pith.paper-citation-record.v1
2408.02900 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 14 of 14 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T22:13:31.695938Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T06:29:37.756724Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

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 b8079369-bdc7-406e-a743-5feb1c43eb59 · inbound

From large language models to multimodal AI: A scoping review on the potential of generative AI in medicine cites this paper.

From large language models to multimodal AI: A scoping review on the potential of generative AI in medicine MedTrinity-25M: A Large-scale Multimodal Dataset with Multigranular Annotations for Medicine

Reference 135

Resolution
unresolved
no resolver link, observed 2026-08-07T22:13:31.695938Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T22:13:31.695938Z digest=sha256:f6ae70cd26d48840a09674770a303554e87fe2aa68f2565ad57b21d74e341d05

Observation 7486be58-79b5-478a-b107-c31d53858cc7 · inbound

Cross-Lingual Pitfalls: Automatic Probing Cross-Lingual Weakness of Multilingual Large Language Models cites this paper.

Cross-Lingual Pitfalls: Automatic Probing Cross-Lingual Weakness of Multilingual Large Language Models MedTrinity-25M: A Large-scale Multimodal Dataset with Multigranular Annotations for Medicine

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:34.221857Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:34.221857Z digest=sha256:64c1a11943a04f2b7026caeacdd15c1cdc188fd1e5a0720be43a7ce7469102e4

Observation 4c4cdb70-7b00-4997-831d-c99d919ca950 · inbound

KokushiMD-10: Benchmark for Evaluating Large Language Models on Ten Japanese National Healthcare Licensing Examinations cites this paper.

KokushiMD-10: Benchmark for Evaluating Large Language Models on Ten Japanese National Healthcare Licensing Examinations MedTrinity-25M: A Large-scale Multimodal Dataset with Multigranular Annotations for Medicine

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-07T05:39:42.506184Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:39:42.506184Z digest=sha256:7792d967382e2f5928c955eb85502266a0c1f199faec4f1de1692f535d5ef1b1

Observation 31afff91-5c0d-4f8b-851b-ed573b3c889e · inbound

Unifying Biomedical Vision-Language Expertise: Towards a Generalist Foundation Model via Multi-CLIP Knowledge Distillation cites this paper.

Unifying Biomedical Vision-Language Expertise: Towards a Generalist Foundation Model via Multi-CLIP Knowledge Distillation MedTrinity-25M: A Large-scale Multimodal Dataset with Multigranular Annotations for Medicine

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-06T22:09:09.710112Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:09:09.710112Z digest=sha256:e16ff95235405b3743fc5c32db2e434ec029ae4eb135fe19982a90c26ddcc9e4

Observation 93861830-7f8f-4e38-842d-996127281bf4 · inbound

Region-Aware Multimodal Large Language Model via SlowFast Tokenization and Pseudo-Mask Guidance for 3D CT Report Generation cites this paper.

Region-Aware Multimodal Large Language Model via SlowFast Tokenization and Pseudo-Mask Guidance for 3D CT Report Generation MedTrinity-25M: A Large-scale Multimodal Dataset with Multigranular Annotations for Medicine

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-06T21:55:46.934947Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:55:46.934947Z digest=sha256:34bd189b215416b5d8f4626cb37ede46317c4d6a9102d0885fab14d8c72fbc80

Observation 60298160-bb4a-4d03-9e2c-2e47c5625230 · inbound

Constructing Ophthalmic MLLM for Positioning-diagnosis Collaboration Through Clinical Cognitive Chain Reasoning cites this paper.

Constructing Ophthalmic MLLM for Positioning-diagnosis Collaboration Through Clinical Cognitive Chain Reasoning MedTrinity-25M: A Large-scale Multimodal Dataset with Multigranular Annotations for Medicine

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-06T14:51:09.886269Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:51:09.886269Z digest=sha256:4e1a5c689ade93ef1954c2e56510a33a0e78457ace04bbf69d95cd9926c06758

Observation 42125ddc-4570-45f7-b84c-5dba5e666f68 · inbound

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine cites this paper.

MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine MedTrinity-25M: A Large-scale Multimodal Dataset with Multigranular Annotations for Medicine

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-06T04:50:45.306820Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T04:50:45.306820Z digest=sha256:17a653624fdeddbfb9f7165b5e10493e66caed60350186516e41e8e8a26828cf

Observation 6ad3ebbe-31a3-4e6f-b5f6-27b38b21d7d6 · inbound

MEDIC-AD: Towards Medical Vision-Language Model's Clinical Intelligence cites this paper.

MEDIC-AD: Towards Medical Vision-Language Model's Clinical Intelligence MedTrinity-25M: A Large-scale Multimodal Dataset with Multigranular Annotations for Medicine

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-02T17:19:39.198283Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T17:19:39.198283Z digest=sha256:c9795851710adb3251014535268e460aaacd55dad9b71047c80e31ef556857a7

Observation f2720386-61c2-4ace-8c1f-00262c4aa714 · inbound

Region-Grounded Report Generation for 3D Medical Imaging: A Fine-Grained Dataset and Graph-Enhanced Framework cites this paper.

Region-Grounded Report Generation for 3D Medical Imaging: A Fine-Grained Dataset and Graph-Enhanced Framework MedTrinity-25M: A Large-scale Multimodal Dataset with Multigranular Annotations for Medicine

Reference 80

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T05:36:01.592487Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-10T05:34:30.894093Z digest=sha256:170c0f794ad4342bb02915515be2f5bca36324909969a8c56ddbe5d78a82b3de

Observation b296d591-f873-4b7d-b1aa-5218d466808f · inbound

CXR-ContraBench: Benchmarking Negated-Option Attraction in Medical VLMs cites this paper.

CXR-ContraBench: Benchmarking Negated-Option Attraction in Medical VLMs MedTrinity-25M: A Large-scale Multimodal Dataset with Multigranular Annotations for Medicine

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-05-11T18:41:09.507531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-08T14:49:53.357083Z digest=sha256:9447315dd3aac11afdaf62ed27f5bdb80fa1d1ffbc9d15d3dbe0ff874cd77a32

Observation f30cdb93-a428-468e-8bbf-b0722b1f2d85 · inbound

MEDLAYXPLAIN: Benchmarking the Expert-Lay Gap in Medical Vision-Language Models cites this paper.

MEDLAYXPLAIN: Benchmarking the Expert-Lay Gap in Medical Vision-Language Models MedTrinity-25M: A Large-scale Multimodal Dataset with Multigranular Annotations for Medicine

Reference 68

Resolution
verified exact
arxiv_id, observed 2026-07-04T06:29:37.758539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-26T14:25:39.363350Z digest=sha256:869bedd583c00c3a2f38f2fb599687f3fed89f841d7ba42ae96ce3f57d215d02

Observation 8d3173ed-4c53-4462-8f65-a51b27e12d82 · inbound

Token-Sparse Medical Multimodal Reasoning via Dual-Stream Reinforcement Learning cites this paper.

Token-Sparse Medical Multimodal Reasoning via Dual-Stream Reinforcement Learning MedTrinity-25M: A Large-scale Multimodal Dataset with Multigranular Annotations for Medicine

Reference 8

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T10:25:41.013976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-07-01T05:36:43.609602Z digest=sha256:0e0ae9d3ba5d0af34610720344541433ba963b98286f1ea24d82b69644153832

Observation 8cce3545-dddb-481e-a310-bfd55eb920c7 · inbound

Towards Enhancing 3D Spatial Reasoning in Medical Multimodal Large Language Models cites this paper.

Towards Enhancing 3D Spatial Reasoning in Medical Multimodal Large Language Models MedTrinity-25M: A Large-scale Multimodal Dataset with Multigranular Annotations for Medicine

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-02T03:31:46.899960Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T03:31:46.899960Z digest=sha256:c71ce7696c4b2478bcfd097734d200ebb160401c5632b69f87953e3fcaa4324a

Observation b2f74418-742a-45d2-9204-429682105ab2 · inbound

TextSLIP: Text Self-Supervised CLIP for Medical Report Generation cites this paper.

TextSLIP: Text Self-Supervised CLIP for Medical Report Generation MedTrinity-25M: A Large-scale Multimodal Dataset with Multigranular Annotations for Medicine

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-01T06:13:04.787463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T06:13:04.787463Z digest=sha256:e822fa94b6ff1a384b61afb0064d100c0b35fb57101d474956343b38fbe13c24