Pith. sign in

Paper Citation Record · LEDGER

Extending nnU-Net is all you need

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2208.10791.

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

pith.paper-citation-record.v1
2208.10791 v1

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 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:50:51.177794Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T22:43:51.139405Z

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 ef7ff873-5d58-4da7-826d-d1ada5527a88 · inbound

A Comprehensive Study on Medical Image Segmentation using Deep Neural Networks cites this paper.

A Comprehensive Study on Medical Image Segmentation using Deep Neural Networks Extending nnU-Net is all you need

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-07T10:50:51.177794Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:50:51.177794Z digest=sha256:e631d0f472cb9f224274d8c1207c3affcc665210be286aeedb2a8d8c510521a9

Observation baba72a7-f9e6-44e0-9f50-b2bd8712aaa3 · inbound

Vision Transformer-Conditioned UNet for Domain-Adaptive Semantic Segmentation cites this paper.

Vision Transformer-Conditioned UNet for Domain-Adaptive Semantic Segmentation Extending nnU-Net is all you need

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-05-20T22:43:51.141680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-20T22:41:41.098660Z digest=sha256:022a2b26fb39fdcb8d367f479047151f8bfe65532eac28e5fcbbabb1b6a1cfa6