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Paper Citation Record · LEDGER

A Two-Stream Mutual Attention Network for Semi-supervised Biomedical Segmentation with Noisy Labels

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1807.11719.

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

pith.paper-citation-record.v1
1807.11719 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T10:46:03.689764Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-14T10:15:41.787784Z

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 fb47836f-300c-4b02-85b7-b28800ca21bb · inbound

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation cites this paper.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation A Two-Stream Mutual Attention Network for Semi-supervised Biomedical Segmentation with Noisy Labels

Reference 88

Resolution
unresolved
no resolver link, observed 2026-08-14T10:46:03.689764Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T10:46:03.689764Z digest=sha256:fc66bd2e9a89366fa60974f306ac68256f2f4fbac894d66640047a735b66b894

Observation 20f6089f-68d4-4c41-b5ec-aa727e854a99 · inbound

Revisiting CycleGAN for semi-supervised segmentation cites this paper.

Revisiting CycleGAN for semi-supervised segmentation A Two-Stream Mutual Attention Network for Semi-supervised Biomedical Segmentation with Noisy Labels

Reference 20

Resolution
verified exact
local_arxiv, observed 2026-08-14T10:15:41.792538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T10:15:41.626927Z digest=sha256:0e165081eb58835ed2b6172f5bb5358c47fe24f4f6ccb79811a2c51843b41810