Pith. sign in

Paper Citation Record · LEDGER

MobileUNETR: A Lightweight End-To-End Hybrid Vision Transformer For Efficient 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:2409.03062.

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

pith.paper-citation-record.v1
2409.03062 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 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:49:04.024976Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T15:33:59.045076Z

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 383089f2-871c-49f9-b9bf-aabb5b89addb · inbound

FORTRESS: Function-composition Optimized Real-Time Resilient Structural Segmentation via Kolmogorov-Arnold Enhanced Spatial Attention Networks cites this paper.

FORTRESS: Function-composition Optimized Real-Time Resilient Structural Segmentation via Kolmogorov-Arnold Enhanced Spatial Attention Networks MobileUNETR: A Lightweight End-To-End Hybrid Vision Transformer For Efficient Medical Image Segmentation

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-06T16:49:04.024976Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:49:04.024976Z digest=sha256:2694d4b2a93a65e388e16a51fa6eff5188d1d9100e8573e1c1bdb16202bcaacb

Observation 66bae766-557a-4aa5-94f7-2e16f9f9fe13 · inbound

SegDT: A Diffusion Transformer-Based Segmentation Model for Medical Imaging cites this paper.

SegDT: A Diffusion Transformer-Based Segmentation Model for Medical Imaging MobileUNETR: A Lightweight End-To-End Hybrid Vision Transformer For Efficient Medical Image Segmentation

Reference 17

Resolution
metadata mismatch
local_arxiv, observed 2026-08-06T15:33:59.050352Z

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=2026-08-06T15:33:58.986019Z digest=sha256:95c71057aaf101dcc9dda73ee14e0f87f82eb341d180110bd933349e9053d2e5