Paper Citation Record · LEDGER

The Liver Tumor Segmentation Benchmark (LiTS)

As of 22 July 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 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 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-07-21T06:31:05.380196+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-26T00:08:20.172801Z

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
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 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 2026-07-21T06:31:05.380196+00:00.

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 2026-07-21T06:31:05.380196+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 2026-07-21T06:31:05.380196+00:00.

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 2026-07-21T06:31:05.380196+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 2026-07-21T06:31:05.380196+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 2026-07-21T06:31:05.380196+00:00.