Paper Citation Record · LEDGER

AutoRG-Brain: Grounded Report Generation for Brain MRI

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2407.16684.

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

pith.paper-citation-record.v1
2407.16684 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:32:54.377652Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T06:59:45.769360Z

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 00c5692e-8691-410b-ae17-a80fca2445af · inbound

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? cites this paper.

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments? AutoRG-Brain: Grounded Report Generation for Brain MRI

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-11T17:03:39.994745Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 90f64e7c-b833-4ad9-861d-8d4ffc00659e · 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 AutoRG-Brain: Grounded Report Generation for Brain MRI

Reference 108

Resolution: unresolved; no resolver link, observed 2026-08-07T22:13:31.235067Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ce17825d-027e-4a19-abf3-30f082ce677a · inbound

Multimodal Large Language Models for Medicine: A Comprehensive Survey cites this paper.

Multimodal Large Language Models for Medicine: A Comprehensive Survey AutoRG-Brain: Grounded Report Generation for Brain MRI

Reference 112

Resolution: unresolved; no resolver link, observed 2026-08-16T05:32:54.377652Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b541d444-9c2d-4a89-a986-e53bbe449c8c · inbound

Are Vision Language Models Ready for Clinical Diagnosis? A 3D Medical Benchmark for Tumor-centric Visual Question Answering cites this paper.

Are Vision Language Models Ready for Clinical Diagnosis? A 3D Medical Benchmark for Tumor-centric Visual Question Answering AutoRG-Brain: Grounded Report Generation for Brain MRI

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T14:26:30.112916Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 81006820-01af-4204-b949-980076001d63 · inbound

Recurrent Visual Feature Extraction and Stereo Attentions for CT Report Generation cites this paper.

Recurrent Visual Feature Extraction and Stereo Attentions for CT Report Generation AutoRG-Brain: Grounded Report Generation for Brain MRI

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-15T18:32:12.258658Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 90d33253-a39c-4e8e-ab22-9b6251f82b08 · inbound

Automatic Fine-grained Segmentation-assisted Report Generation cites this paper.

Automatic Fine-grained Segmentation-assisted Report Generation AutoRG-Brain: Grounded Report Generation for Brain MRI

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T15:13:05.616646Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b5e896f8-ca8e-48b0-bade-cfad7514f84f · inbound

AMRG: Extend Vision Language Models for Automatic Mammography Report Generation cites this paper.

AMRG: Extend Vision Language Models for Automatic Mammography Report Generation AutoRG-Brain: Grounded Report Generation for Brain MRI

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-15T17:39:55.975961Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd58b2d1-e58f-4492-b9c5-561841e8168f · inbound

NeuroQA: A Large-Scale Image-Grounded Benchmark for 3D Brain MRI Understanding cites this paper.

NeuroQA: A Large-Scale Image-Grounded Benchmark for 3D Brain MRI Understanding AutoRG-Brain: Grounded Report Generation for Brain MRI

Reference 50

Resolution: verified exact; arxiv_id, observed 2026-05-21T06:59:45.771035Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 6b764f47-1693-4582-bfde-3b6604be781c · inbound

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

TextSLIP: Text Self-Supervised CLIP for Medical Report Generation AutoRG-Brain: Grounded Report Generation for Brain MRI

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-01T06:13:03.436772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.