Paper Citation Record · LEDGER

m2caiSeg: Semantic Segmentation of Laparoscopic Images using Convolutional Neural Networks

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2008.10134.

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

pith.paper-citation-record.v1
2008.10134 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:20:01.826147Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T20:22:50.669602Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
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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 db1807c7-8640-47f0-bac3-a24af135774f · inbound

MARL-MambaContour: Unleashing Multi-Agent Deep Reinforcement Learning for Active Contour Optimization in Medical Image Segmentation cites this paper.

MARL-MambaContour: Unleashing Multi-Agent Deep Reinforcement Learning for Active Contour Optimization in Medical Image Segmentation m2caiSeg: Semantic Segmentation of Laparoscopic Images using Convolutional Neural Networks

Reference 103

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:01.826147Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cce3a26d-b517-4c25-99c0-ce275d97bc29 · inbound

Is Visual in-Context Learning for Compositional Medical Tasks within Reach? cites this paper.

Is Visual in-Context Learning for Compositional Medical Tasks within Reach? m2caiSeg: Semantic Segmentation of Laparoscopic Images using Convolutional Neural Networks

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-06T21:12:05.951336Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c157bdd-6b49-47d1-a839-c534eb2f6f17 · inbound

Dino U-Net: Exploiting High-Fidelity Dense Features from Foundation Models for Medical Image Segmentation cites this paper.

Dino U-Net: Exploiting High-Fidelity Dense Features from Foundation Models for Medical Image Segmentation m2caiSeg: Semantic Segmentation of Laparoscopic Images using Convolutional Neural Networks

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-18T20:22:50.673017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 6ba67db0-b999-40d9-98ec-e94afeb35dae · inbound

Current validation practice undermines surgical AI development cites this paper.

Current validation practice undermines surgical AI development m2caiSeg: Semantic Segmentation of Laparoscopic Images using Convolutional Neural Networks

Reference 83

Resolution: verified exact; arxiv_id, observed 2026-05-18T01:42:17.474629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 801bd23c-d565-48be-b969-987b778efccb · inbound

Current validation practice undermines surgical AI development cites this paper.

Current validation practice undermines surgical AI development m2caiSeg: Semantic Segmentation of Laparoscopic Images using Convolutional Neural Networks

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-03T23:55:25.398363Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a4369137-fb50-48ee-aab2-babb32137843 · inbound

Unlocking Positive Transfer in Incrementally Learning Surgical Instruments: A Self-reflection Hierarchical Prompt Framework cites this paper.

Unlocking Positive Transfer in Incrementally Learning Surgical Instruments: A Self-reflection Hierarchical Prompt Framework m2caiSeg: Semantic Segmentation of Laparoscopic Images using Convolutional Neural Networks

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-13T21:03:20.370387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9d13ed2a-9006-4ca9-8ad8-2c4aeb8b28bd · inbound

Probing Intrinsic Medical Task Relationships: A Contrastive Learning Perspective cites this paper.

Probing Intrinsic Medical Task Relationships: A Contrastive Learning Perspective m2caiSeg: Semantic Segmentation of Laparoscopic Images using Convolutional Neural Networks

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-05-10T22:25:50.174780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.