Paper Citation Record · LEDGER

MedLiteNet: Lightweight Hybrid Medical Image Segmentation Model

As of 21 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:2509.03041.

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

pith.paper-citation-record.v1
2509.03041 v1

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T11:12:15.061138Z

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

20 of 20 outbound references displayed

verified exact0
verified fuzzy3
unresolved17
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 193317cc-5d4a-470d-8529-39fd6b85c3da · outbound

This paper cites Recurrent Residual Convolutional Neural Network based on U-Net (R2U-Net) for Medical Image Segmentation.

MedLiteNet: Lightweight Hybrid Medical Image Segmentation Model Recurrent Residual Convolutional Neural Network based on U-Net (R2U-Net) for Medical Image Segmentation

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-05T11:12:14.997372Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d1789b22-db29-41e9-b967-1a7200484f18 · outbound

This paper cites Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation.

MedLiteNet: Lightweight Hybrid Medical Image Segmentation Model Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-05T11:12:15.001384Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3709dbc7-74a9-492c-b802-f9101b21fa83 · outbound

This paper cites an unresolved cited work.

MedLiteNet: Lightweight Hybrid Medical Image Segmentation Model Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-05T11:12:15.275155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 72639828-ade6-4b3c-bce4-37b0961b6cdb · outbound

This paper cites TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation.

MedLiteNet: Lightweight Hybrid Medical Image Segmentation Model TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-05T11:12:15.009876Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b080af72-327b-4bee-9f83-a706de837b2e · outbound

This paper cites Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC).

MedLiteNet: Lightweight Hybrid Medical Image Segmentation Model Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC)

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-05T11:12:15.013645Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1a2bf7f7-20f1-491c-b0c6-f27fea421263 · outbound

This paper cites an unresolved cited work.

MedLiteNet: Lightweight Hybrid Medical Image Segmentation Model Unresolved cited work

Reference 6

Resolution: unresolved; raw_fallback, observed 2026-08-05T11:12:15.265913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f980af0a-4c06-46a1-ba8b-b184b3702f95 · outbound

This paper cites an unresolved cited work.

MedLiteNet: Lightweight Hybrid Medical Image Segmentation Model Unresolved cited work

Reference 7

Resolution: unresolved; raw_fallback, observed 2026-08-05T11:12:15.256264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 202699d2-f73f-4b98-9457-621717051042 · outbound

This paper cites an unresolved cited work.

MedLiteNet: Lightweight Hybrid Medical Image Segmentation Model Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-08-05T11:12:15.246777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6989f024-7ef0-4901-bb63-02a269a3c8da · outbound

This paper cites an unresolved cited work.

MedLiteNet: Lightweight Hybrid Medical Image Segmentation Model Unresolved cited work

Reference 9

Resolution: unresolved; raw_fallback, observed 2026-08-05T11:12:15.237329Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 520bf804-192b-43a5-8a35-99c19f808213 · outbound

This paper cites Attention U-Net: Learning Where to Look for the Pancreas.

MedLiteNet: Lightweight Hybrid Medical Image Segmentation Model Attention U-Net: Learning Where to Look for the Pancreas

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-05T11:12:15.030885Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a000bb30-c3b8-4186-9106-56ae3cea9708 · outbound

This paper cites an unresolved cited work.

MedLiteNet: Lightweight Hybrid Medical Image Segmentation Model Unresolved cited work

Reference 11

Resolution: unresolved; raw_fallback, observed 2026-08-05T11:12:15.227909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f558f0cd-e18d-4eb5-b956-bd9656a05746 · outbound

This paper cites Squeeze & Excitation.

MedLiteNet: Lightweight Hybrid Medical Image Segmentation Model Squeeze & Excitation

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:12:15.218373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 93b7fba0-418d-4f09-91c4-053abb0f93d4 · outbound

This paper cites an unresolved cited work.

MedLiteNet: Lightweight Hybrid Medical Image Segmentation Model Unresolved cited work

Reference 13

Resolution: unresolved; raw_fallback, observed 2026-08-05T11:12:15.208593Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d057e71c-1a9f-4b72-b803-85f32bd7d02e · outbound

This paper cites an unresolved cited work.

MedLiteNet: Lightweight Hybrid Medical Image Segmentation Model Unresolved cited work

Reference 14

Resolution: unresolved; raw_fallback, observed 2026-08-05T11:12:15.199054Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation fb868156-f1bc-4220-955b-de1053095bc2 · outbound

This paper cites an unresolved cited work.

MedLiteNet: Lightweight Hybrid Medical Image Segmentation Model Unresolved cited work

Reference 15

Resolution: unresolved; raw_fallback, observed 2026-08-05T11:12:15.189579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 222f7d1a-589f-44d7-997a-863dee9cf9fb · outbound

This paper cites an unresolved cited work.

MedLiteNet: Lightweight Hybrid Medical Image Segmentation Model Unresolved cited work

Reference 16

Resolution: unresolved; raw_fallback, observed 2026-08-05T11:12:15.179217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5c67d15a-fe94-4387-bcdf-580ea0537d29 · outbound

This paper cites A., et al.

MedLiteNet: Lightweight Hybrid Medical Image Segmentation Model A., et al

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:12:15.169689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6c00c308-ae4b-468d-97fd-ec24d56e4ce7 · outbound

This paper cites an unresolved cited work.

MedLiteNet: Lightweight Hybrid Medical Image Segmentation Model Unresolved cited work

Reference 18

Resolution: unresolved; raw_fallback, observed 2026-08-05T11:12:15.158721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation deb75258-7af8-40e4-86c4-7943a7f183c2 · outbound

This paper cites N., & Lopez-Paz, D.

MedLiteNet: Lightweight Hybrid Medical Image Segmentation Model N., & Lopez-Paz, D

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:12:15.148947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 456ab737-3422-43d0-8d01-f31190b65548 · outbound

This paper cites an unresolved cited work.

MedLiteNet: Lightweight Hybrid Medical Image Segmentation Model Unresolved cited work

Reference 20

Resolution: unresolved; raw_fallback, observed 2026-08-05T11:12:15.138338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Pith citing papers

No inbound Pith citation observations are available.