Pith. sign in

Paper Citation Record · LEDGER

m2caiSeg: Semantic Segmentation of Laparoscopic Images using Convolutional Neural Networks

As of 10 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 2026-08-10T06:31:04.303077+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
  • 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 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.

source=pdf_text observed=2026-08-06T23:20:01.826147Z digest=sha256:273f2dffbf7c87fd3c26909a230ba6ed67091b2e5f30212563ca4a0fafc24402

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.

source=pdf_text observed=2026-08-06T21:12:05.951336Z digest=sha256:b37828865850ab7da18b3bd9c704181c012498e7c753efb31d1102b376e37b48

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-18T20:22:41.555806Z digest=sha256:a77df2ad0aa9b04c811efa8a0bd2208b50541897fefec011decc77320ab4fdd1

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-18T01:41:38.726003Z digest=sha256:ec816a74e2c0237635a0b5d1e7573af7d327b5a9e59997e0dc8eb1de1c8e28dd

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.

source=pdf_text observed=2026-08-03T23:55:25.398363Z digest=sha256:0ee123e0f1a182bd5eec15b2736427ea893231af402457cd9636ca6fc1925132

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-13T20:58:29.515826Z digest=sha256:58326688cd1617537f4326e92cc268576dcb22b199626ab5ba475a2bd27ae823

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T19:54:48.926387Z digest=sha256:7bd228575ae469e64fd193a51cea9db556f8f2e1cd6cffea7f8e8b804d08173f