Paper Citation Record · LEDGER

ESA: Annotation-Efficient Active Learning for Semantic Segmentation

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2408.13491.

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

pith.paper-citation-record.v1
2408.13491 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T18:19:39.279026Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T03:39:30.078025Z

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 f55303f0-05f4-4cb6-965e-04d10eec7d69 · inbound

MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction cites this paper.

MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction ESA: Annotation-Efficient Active Learning for Semantic Segmentation

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-09T18:19:39.279026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d1feccaa-40b0-4394-b403-7c0646b2da79 · inbound

A Novel Convolutional-Free Method for 3D Medical Imaging Segmentation cites this paper.

A Novel Convolutional-Free Method for 3D Medical Imaging Segmentation ESA: Annotation-Efficient Active Learning for Semantic Segmentation

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-08T19:33:21.428268Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7cb7746f-9ec0-4cb9-8d8b-e2c4ac40b900 · inbound

SSS: Semi-Supervised SAM-2 with Efficient Prompting for Medical Imaging Segmentation cites this paper.

SSS: Semi-Supervised SAM-2 with Efficient Prompting for Medical Imaging Segmentation ESA: Annotation-Efficient Active Learning for Semantic Segmentation

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T05:03:33.053447Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 90ea67e6-cb26-49c4-b5ac-feed1af0e81b · inbound

Speeding up the annotation process in semantic segmentation industrial applications cites this paper.

Speeding up the annotation process in semantic segmentation industrial applications ESA: Annotation-Efficient Active Learning for Semantic Segmentation

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-07-04T03:39:30.079717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.