Paper Citation Record · LEDGER

MAIS: Memory-Attention for Interactive Segmentation

As of 21 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2505.07511.

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

pith.paper-citation-record.v1
2505.07511 v1

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:18:37.887695Z

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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

19 of 19 outbound references displayed

verified exact0
verified fuzzy7
unresolved12
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 47db2e63-0917-42d7-9573-c6ca86cf8697 · outbound

This paper cites an unresolved cited work.

MAIS: Memory-Attention for Interactive Segmentation Unresolved cited work

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-15T22:18:37.390671Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7929020f-3b3a-49dd-ac24-f0110834c335 · outbound

This paper cites SAM3D: Segment Anything Model in Volumetric Medical Images.

MAIS: Memory-Attention for Interactive Segmentation SAM3D: Segment Anything Model in Volumetric Medical Images

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-15T22:18:37.417807Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d6e7a0a0-c775-410f-89d8-7ce6d4b45816 · outbound

This paper cites SAM on Medical Images: A Comprehensive Study on Three Prompt Modes.

MAIS: Memory-Attention for Interactive Segmentation SAM on Medical Images: A Comprehensive Study on Three Prompt Modes

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-15T22:18:37.521600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c76f81ba-ccc5-4bc4-97c1-a9284ec51a35 · outbound

This paper cites Monai label: A framework for ai-assisted interactive labeling of 3d medical images.

MAIS: Memory-Attention for Interactive Segmentation Monai label: A framework for ai-assisted interactive labeling of 3d medical images

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:18:38.587408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 97fb8d0f-e0fa-40ca-8ef4-df77abe89091 · outbound

This paper cites SegVol: Universal and Interactive Volumetric Medical Image Segmentation.

MAIS: Memory-Attention for Interactive Segmentation SegVol: Universal and Interactive Volumetric Medical Image Segmentation

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-15T22:18:37.533998Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1db4bcf5-908e-419a-b875-97c0d938181c · outbound

This paper cites 3DSAM-adapter: Holistic adaptation of SAM from 2D to 3D for promptable tumor segmentation.

MAIS: Memory-Attention for Interactive Segmentation 3DSAM-adapter: Holistic adaptation of SAM from 2D to 3D for promptable tumor segmentation

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-15T22:18:37.539959Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 515868a8-3b20-4efc-8f52-afcedf1ea9ef · outbound

This paper cites Swin unetr: Swin transformers for semantic segmentation of brain tumors in mri images.

MAIS: Memory-Attention for Interactive Segmentation Swin unetr: Swin transformers for semantic segmentation of brain tumors in mri images

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:18:38.567975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9ae9e3ba-6273-4c45-adc8-1bc118efc8c0 · outbound

This paper cites Unetr: Transformers for 3d medical image segmentation.

MAIS: Memory-Attention for Interactive Segmentation Unetr: Transformers for 3d medical image segmentation

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-15T22:18:37.550333Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b3c7963a-60e1-40e3-b8b6-42dd94fa6ca3 · outbound

This paper cites nnu-net: a self-configuring method for deep learning-based biomedical image segmentation.

MAIS: Memory-Attention for Interactive Segmentation nnu-net: a self-configuring method for deep learning-based biomedical image segmentation

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-15T22:18:37.556791Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 34baff78-62fa-49cb-8dae-34933ed4ded3 · outbound

This paper cites Amos: A large-scale abdominal multi-organ benchmark for versatile medical image segmentation.

MAIS: Memory-Attention for Interactive Segmentation Amos: A large-scale abdominal multi-organ benchmark for versatile medical image segmentation

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:18:38.516108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 42883f5e-e79e-4867-b536-5ae005a0713b · outbound

This paper cites Segment anything.

MAIS: Memory-Attention for Interactive Segmentation Segment anything

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-15T22:18:37.567793Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5aae5048-9d9d-478d-b15b-29a746b1ee1c · outbound

This paper cites Promise: Prompt-driven 3d medical image segmentation using pretrained image foundation models.

MAIS: Memory-Attention for Interactive Segmentation Promise: Prompt-driven 3d medical image segmentation using pretrained image foundation models

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:18:38.476875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 40d3b23a-aa28-45d9-8c3c-2aa5108d3b8f · outbound

This paper cites Segment anything in medical images.

MAIS: Memory-Attention for Interactive Segmentation Segment anything in medical images

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-15T22:18:37.578856Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d42335e-d2d5-4797-87ce-5d99200f6040 · outbound

This paper cites Segment anything model for medical image analysis: an experimental study.

MAIS: Memory-Attention for Interactive Segmentation Segment anything model for medical image analysis: an experimental study

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-15T22:18:37.584254Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 66f375a9-db0c-43c1-b223-d0114eadfe9c · outbound

This paper cites Han-seg: The head and neck organ-at-risk ct and mr segmentation challenge.

MAIS: Memory-Attention for Interactive Segmentation Han-seg: The head and neck organ-at-risk ct and mr segmentation challenge

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:18:38.331224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation aea2c0bf-9710-4591-a36c-203e44caecc6 · outbound

This paper cites SAM 2: Segment Anything in Images and Videos.

MAIS: Memory-Attention for Interactive Segmentation SAM 2: Segment Anything in Images and Videos

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-15T22:18:37.594516Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9cfdf46b-01b4-43c8-9e9c-fe0bf831568a · outbound

This paper cites Sam-clip: Merging vision foundation models towards semantic and spatial understanding.

MAIS: Memory-Attention for Interactive Segmentation Sam-clip: Merging vision foundation models towards semantic and spatial understanding

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:18:38.281368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3d8df72c-027d-4bff-8882-af422e651393 · outbound

This paper cites SAM-Med3D: Towards General-purpose Segmentation Models for Volumetric Medical Images.

MAIS: Memory-Attention for Interactive Segmentation SAM-Med3D: Towards General-purpose Segmentation Models for Volumetric Medical Images

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-15T22:18:37.796898Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e374cffe-1569-420b-af4b-a8dbad20e3bc · outbound

This paper cites Totalsegmentator: robust segmentation of 104 anatomic structures in ct images.

MAIS: Memory-Attention for Interactive Segmentation Totalsegmentator: robust segmentation of 104 anatomic structures in ct images

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:18:38.263295Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Pith citing papers

No inbound Pith citation observations are available.