Paper Citation Record · LEDGER

The Liver Tumor Segmentation Benchmark (LiTS)

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 21 inbound Pith citation observations for arXiv:1901.04056.

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

pith.paper-citation-record.v1
1901.04056 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 21 of 21 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 21 of 21 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T14:54:34.677111Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T16:49:58.518483Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
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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 89621c92-ec46-4112-80ce-e3a9356c85d7 · inbound

A Deep Regression Model for Seed Identification in Prostate Brachytherapy cites this paper.

A Deep Regression Model for Seed Identification in Prostate Brachytherapy The Liver Tumor Segmentation Benchmark (LiTS)

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-25T16:41:02.415660Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3d406625-a48b-4fbc-8111-ddf552b78e8a · inbound

An attempt at beating the 3D U-Net cites this paper.

An attempt at beating the 3D U-Net The Liver Tumor Segmentation Benchmark (LiTS)

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-14T14:54:34.677111Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e2f1750-1df0-4dad-9b0b-7602259ab391 · inbound

Mask Mining for Improved Liver Lesion Segmentation cites this paper.

Mask Mining for Improved Liver Lesion Segmentation The Liver Tumor Segmentation Benchmark (LiTS)

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-14T13:27:30.357624Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e930b954-9930-4a05-bf6e-37350d88b8db · inbound

KLDivNet: An unsupervised neural network for multi-modality image registration cites this paper.

KLDivNet: An unsupervised neural network for multi-modality image registration The Liver Tumor Segmentation Benchmark (LiTS)

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-14T11:35:05.880887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb1c83e3-2ab1-47ff-965a-a1f4e6d05511 · inbound

MultiverSeg: Scalable Interactive Segmentation of Biomedical Imaging Datasets with In-Context Guidance cites this paper.

MultiverSeg: Scalable Interactive Segmentation of Biomedical Imaging Datasets with In-Context Guidance The Liver Tumor Segmentation Benchmark (LiTS)

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-11T11:43:08.412417Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dab96cfc-d07d-4d83-9a8c-f295375e5f90 · inbound

RadGPT: Constructing 3D Image-Text Tumor Datasets cites this paper.

RadGPT: Constructing 3D Image-Text Tumor Datasets The Liver Tumor Segmentation Benchmark (LiTS)

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-10T21:31:28.418997Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 531f4197-d213-4dd9-843c-49170cc49a0a · inbound

Deep Distance Map Regression Network with Shape-aware Loss for Imbalanced Medical Image Segmentation cites this paper.

Deep Distance Map Regression Network with Shape-aware Loss for Imbalanced Medical Image Segmentation The Liver Tumor Segmentation Benchmark (LiTS)

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-10T20:15:38.946292Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 113a939d-0fa2-4d5c-b577-1812e7e57bbe · 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 The Liver Tumor Segmentation Benchmark (LiTS)

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T14:26:28.961837Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1455f798-8781-416e-bb92-20ab2f1d837b · inbound

Automated MRI Tumor Segmentation using hybrid U-Net with Transformer and Efficient Attention cites this paper.

Automated MRI Tumor Segmentation using hybrid U-Net with Transformer and Efficient Attention The Liver Tumor Segmentation Benchmark (LiTS)

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T23:55:43.692688Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 51709eb6-247b-4946-a2c1-779de87e82e6 · inbound

PanTS: The Pancreatic Tumor Segmentation Dataset cites this paper.

PanTS: The Pancreatic Tumor Segmentation Dataset The Liver Tumor Segmentation Benchmark (LiTS)

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T21:02:28.649938Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 952c2378-b383-4b63-8874-85675c411afc · inbound

Learning Segmentation from Radiology Reports cites this paper.

Learning Segmentation from Radiology Reports The Liver Tumor Segmentation Benchmark (LiTS)

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T19:30:53.355156Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b8a42ee-1cb9-44e0-9d84-8b3abc005954 · inbound

Q-Former Autoencoder: A Modern Framework for Medical Anomaly Detection cites this paper.

Q-Former Autoencoder: A Modern Framework for Medical Anomaly Detection The Liver Tumor Segmentation Benchmark (LiTS)

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T14:37:12.415825Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c5f80fce-cec9-4e49-8328-3636b4bb67ef · inbound

Uncertainty-Aware Segmentation Quality Prediction via Deep Learning Bayesian Modeling: Comprehensive Evaluation and Interpretation on Skin Cancer and Liver Segmentation cites this paper.

Uncertainty-Aware Segmentation Quality Prediction via Deep Learning Bayesian Modeling: Comprehensive Evaluation and Interpretation on Skin Cancer and Liver Segmentation The Liver Tumor Segmentation Benchmark (LiTS)

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-06T05:38:16.264372Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 60240d76-dcde-4878-9663-f8816cfa5e79 · inbound

Optimal Linear Baseline Models for Scientific Machine Learning cites this paper.

Optimal Linear Baseline Models for Scientific Machine Learning The Liver Tumor Segmentation Benchmark (LiTS)

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-05T23:19:28.286189Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 56274cf9-4a1f-4cf1-a214-aa02f51e8120 · inbound

DIET-CP: Lightweight and Data Efficient Self Supervised Continued Pretraining cites this paper.

DIET-CP: Lightweight and Data Efficient Self Supervised Continued Pretraining The Liver Tumor Segmentation Benchmark (LiTS)

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-05T11:31:41.970084Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 884b003b-90ef-4669-a5f0-d2ce9bd9f5c1 · inbound

MAE-SAM2: Mask Autoencoder-Enhanced SAM2 for Clinical Retinal Vascular Leakage Segmentation cites this paper.

MAE-SAM2: Mask Autoencoder-Enhanced SAM2 for Clinical Retinal Vascular Leakage Segmentation The Liver Tumor Segmentation Benchmark (LiTS)

Reference 8

Resolution: metadata mismatch; arxiv_id, observed 2026-05-18T17:52:46.181201Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 14c7e603-acc6-4044-a517-cf410e5a1aaa · inbound

Beyond Classification Accuracy: Neural-MedBench and the Need for Deeper Reasoning Benchmarks cites this paper.

Beyond Classification Accuracy: Neural-MedBench and the Need for Deeper Reasoning Benchmarks The Liver Tumor Segmentation Benchmark (LiTS)

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-18T13:31:25.626354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 66dce54f-f853-4ee2-ae4a-7ee7850ef6b8 · inbound

Towards Continuous-variable Quantum Neural Networks for Biomedical Imaging cites this paper.

Towards Continuous-variable Quantum Neural Networks for Biomedical Imaging The Liver Tumor Segmentation Benchmark (LiTS)

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-04T00:22:10.590657Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6ddccc98-0b96-48a7-9046-5650f6e200e8 · inbound

DeepTumorVQA: A Hierarchical 3D CT Benchmark for Stage-Wise Evaluation of Medical VLMs and Tool-Augmented Agents cites this paper.

DeepTumorVQA: A Hierarchical 3D CT Benchmark for Stage-Wise Evaluation of Medical VLMs and Tool-Augmented Agents The Liver Tumor Segmentation Benchmark (LiTS)

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-12T06:41:43.551928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 73d239a7-d2fb-4533-a10f-225136159a2a · inbound

RadThinking: A Dataset for Longitudinal Clinical Reasoning in Radiology cites this paper.

RadThinking: A Dataset for Longitudinal Clinical Reasoning in Radiology The Liver Tumor Segmentation Benchmark (LiTS)

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-12T03:56:21.651008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 973614a7-c65f-4b3b-bdcd-617e839df378 · inbound

BenchX: Benchmarking AI Models for Cancer Detection and Localization with Demographic and Protocol Biases cites this paper.

BenchX: Benchmarking AI Models for Cancer Detection and Localization with Demographic and Protocol Biases The Liver Tumor Segmentation Benchmark (LiTS)

Reference 9

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T16:49:58.520180Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.