Pith. sign in

Paper Citation Record · LEDGER

D-Net: Dynamic Large Kernel with Dynamic Feature Fusion for Volumetric Medical Image Segmentation

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2403.10674.

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

pith.paper-citation-record.v1
2403.10674 v2

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 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:53:59.938128Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T17:35:24.539459Z

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 80a0ca4c-e54a-4752-9de6-89cfd7737495 · inbound

MS-UMamba: An Improved Vision Mamba Unet for Fetal Abdominal Medical Image Segmentation cites this paper.

MS-UMamba: An Improved Vision Mamba Unet for Fetal Abdominal Medical Image Segmentation D-Net: Dynamic Large Kernel with Dynamic Feature Fusion for Volumetric Medical Image Segmentation

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-07T00:53:59.938128Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:53:59.938128Z digest=sha256:9180c9ff2d0fb13d2c2ad14eb9a9e21869821bcc9af8d5a393b8c7595443ea91

Observation 54afb95b-1a72-489d-ad3b-017bde4ca2ba · inbound

RAPNet: A Receptive-Field Adaptive Convolutional Neural Network for Pansharpening cites this paper.

RAPNet: A Receptive-Field Adaptive Convolutional Neural Network for Pansharpening D-Net: Dynamic Large Kernel with Dynamic Feature Fusion for Volumetric Medical Image Segmentation

Reference 10

Resolution
verified exact
local_arxiv, observed 2026-08-06T17:35:24.559383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:35:24.501430Z digest=sha256:b96b4d139848bab2441f1ef7b7f0f63db3d17c52f1ea4cb1246bfbeea301fea6