Paper Citation Record · LEDGER

A Comparison and Evaluation of Fine-tuned Convolutional Neural Networks to Large Language Models for Image Classification and Segmentation of Brain Tumors on MRI

As of 11 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 1 inbound Pith citation observation for arXiv:2509.10683.

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

pith.paper-citation-record.v1
2509.10683 v1

Coverage vector

measured 12 of 12 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T17:43:17.764278Z

measured 13 of 13 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 2026-05-10T08:25:57.646822Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-10T08:27:51.888209Z

Reference resolution

12 of 12 outbound references displayed

verified exact2
verified fuzzy0
unresolved9
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 36c38b4b-2586-4be5-b281-60373740584f · outbound

This paper cites Lung Disease Classification using Deep Convolutional Neural Network.

A Comparison and Evaluation of Fine-tuned Convolutional Neural Networks to Large Language Models for Image Classification and Segmentation of Brain Tumors on MRI Lung Disease Classification using Deep Convolutional Neural Network

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-04T17:43:17.729321Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 298f19cb-8421-444a-a90a-8dba55d2cbdc · outbound

This paper cites Deep cnn for brain tumor classification.Neural processing letters, 53(1):671–700, 2021.

A Comparison and Evaluation of Fine-tuned Convolutional Neural Networks to Large Language Models for Image Classification and Segmentation of Brain Tumors on MRI Deep cnn for brain tumor classification.Neural processing letters, 53(1):671–700, 2021

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-04T17:43:17.733202Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d64fb1a3-0daf-4a10-8794-9b445ce89933 · outbound

This paper cites Brain tumor segmentation based on deep learning and an attention mechanism using MRI multi-modalities brain images.Scientific Reports, 11 (1):10930, May 2021.

A Comparison and Evaluation of Fine-tuned Convolutional Neural Networks to Large Language Models for Image Classification and Segmentation of Brain Tumors on MRI Brain tumor segmentation based on deep learning and an attention mechanism using MRI multi-modalities brain images.Scientific Reports, 11 (1):10930, May 2021

Reference 3

Resolution: verified exact; doi, observed 2026-08-04T17:43:59.418991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 37900ebd-d690-498b-85d4-3614de09c9d7 · outbound

This paper cites Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge.

A Comparison and Evaluation of Fine-tuned Convolutional Neural Networks to Large Language Models for Image Classification and Segmentation of Brain Tumors on MRI Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-04T17:43:17.739406Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 417a18cf-fa55-45c3-8a26-772f87329170 · outbound

This paper cites Kirby, John B.

A Comparison and Evaluation of Fine-tuned Convolutional Neural Networks to Large Language Models for Image Classification and Segmentation of Brain Tumors on MRI Kirby, John B

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-04T17:43:17.743738Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 735959e4-63d7-4c74-a027-b04ac3f21dae · outbound

This paper cites an unresolved cited work.

A Comparison and Evaluation of Fine-tuned Convolutional Neural Networks to Large Language Models for Image Classification and Segmentation of Brain Tumors on MRI Unresolved cited work

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-04T17:43:17.746819Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3db35580-aee3-480a-9c0c-aded4a9d69f1 · outbound

This paper cites Bakas, H.

A Comparison and Evaluation of Fine-tuned Convolutional Neural Networks to Large Language Models for Image Classification and Segmentation of Brain Tumors on MRI Bakas, H

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-04T17:43:17.753053Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8e331ccf-e628-4254-8476-7e2166acc932 · outbound

This paper cites URL https://www.cancerimagingarchive.net/ analysis-result/brats-tcga-lgg/.

A Comparison and Evaluation of Fine-tuned Convolutional Neural Networks to Large Language Models for Image Classification and Segmentation of Brain Tumors on MRI URL https://www.cancerimagingarchive.net/ analysis-result/brats-tcga-lgg/

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-04T17:43:17.755846Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 18bacfb8-ddce-4b83-bb25-a1334fc69374 · outbound

This paper cites an unresolved cited work.

A Comparison and Evaluation of Fine-tuned Convolutional Neural Networks to Large Language Models for Image Classification and Segmentation of Brain Tumors on MRI Unresolved cited work

Reference 9

Resolution: verified exact; doi, observed 2026-08-04T17:43:59.210483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 528d359d-9f97-4558-bd2d-6c0b61245215 · outbound

This paper cites Berg, Wan-Yen Lo, Piotr Dollár, and Ross Girshick.

A Comparison and Evaluation of Fine-tuned Convolutional Neural Networks to Large Language Models for Image Classification and Segmentation of Brain Tumors on MRI Berg, Wan-Yen Lo, Piotr Dollár, and Ross Girshick

Reference 10

Resolution: malformed identifier; no resolver link, observed 2026-08-04T17:43:17.761480Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d01f54d7-4fa0-49ac-bc9f-7eb0e8077ba0 · outbound

This paper cites LLaFS: When Large Language Models Meet Few-Shot Segmentation.

A Comparison and Evaluation of Fine-tuned Convolutional Neural Networks to Large Language Models for Image Classification and Segmentation of Brain Tumors on MRI LLaFS: When Large Language Models Meet Few-Shot Segmentation

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-04T17:43:17.764278Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c312a99f-960a-4437-bc5a-9cd0a5d74f1a · outbound

This paper cites doi: 10.1109/TMI.2014.2377694.

A Comparison and Evaluation of Fine-tuned Convolutional Neural Networks to Large Language Models for Image Classification and Segmentation of Brain Tumors on MRI doi: 10.1109/TMI.2014.2377694

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-04T17:43:17.750302Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 0936ec06-1b40-4acd-9b81-a1b878fcf154 · inbound

Agentic Large Language Models for Training-Free Neuro-Radiological Image Analysis cites this paper.

Agentic Large Language Models for Training-Free Neuro-Radiological Image Analysis A Comparison and Evaluation of Fine-tuned Convolutional Neural Networks to Large Language Models for Image Classification and Segmentation of Brain Tumors on MRI

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-10T08:27:51.889532Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.