Paper Citation Record · LEDGER

Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data

As of 9 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 1 inbound Pith citation observation for arXiv:2506.24039.

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

pith.paper-citation-record.v1
2506.24039 v2

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:29:02.824750Z

measured 30 of 30 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-12T01:18:11.157463Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T08:06:29.312410Z

Reference resolution

29 of 29 outbound references displayed

verified exact2
verified fuzzy22
unresolved5
parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 760da727-d9b4-4d0b-a4be-0a583d5aff16 · outbound

This paper cites Segment anything for microscopy.

Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data Segment anything for microscopy

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:29:09.206486Z

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Observation ed1eec7d-edd0-42f6-a515-ffacfbcdbec2 · outbound

This paper cites Emerging properties in self- supervised vision transformers.

Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data Emerging properties in self- supervised vision transformers

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:29:08.965702Z

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Observation 818ca449-fd51-433e-8b39-9c5efe32374d · outbound

This paper cites Carpenter, Thouis R.

Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data Carpenter, Thouis R

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:29:08.698025Z

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Observation 57c81d51-c1dd-4421-99d7-fec9d9f18824 · outbound

This paper cites Lienkamp, Thomas Brox, and Olaf Ronneberger.

Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data Lienkamp, Thomas Brox, and Olaf Ronneberger

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:29:08.395624Z

Source-reported events for the cited work

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Observation b5d7bda4-8d51-44a8-9b23-854296ae6e77 · outbound

This paper cites Measures of the amount of ecologic as- sociation between species.

Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data Measures of the amount of ecologic as- sociation between species

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:29:08.158911Z

Source-reported events for the cited work

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Observation 99a1e18b-a48f-4b55-8632-10b1cceea941 · outbound

This paper cites The pascal visual object classes (voc) challenge.

Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data The pascal visual object classes (voc) challenge

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:29:07.897053Z

Source-reported events for the cited work

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Observation 5699695b-6e22-4cc2-892c-df318dc57328 · outbound

This paper cites Achieving the hydrogen shot: Interrogating ionomer interfaces.

Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data Achieving the hydrogen shot: Interrogating ionomer interfaces

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:29:07.639622Z

Source-reported events for the cited work

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Observation dcf72ca6-863b-45cd-a54f-932a03bb1327 · outbound

This paper cites Deep learning analysis on microscopic imag- ing in materials science.

Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data Deep learning analysis on microscopic imag- ing in materials science

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:29:07.360617Z

Source-reported events for the cited work

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Observation 5bb08689-1f96-403d-b57d-3b2658344c61 · outbound

This paper cites VISTA3D: A Unified Segmenta- tion Foundation Model For 3D Medical Imaging.

Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data VISTA3D: A Unified Segmenta- tion Foundation Model For 3D Medical Imaging

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:29:07.132275Z

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 eb22666f-f30f-4012-b2b0-d55abfa949a0 · outbound

This paper cites Data readiness for ai: A 360-degree survey.

Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data Data readiness for ai: A 360-degree survey

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:29:06.870256Z

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 6d66a785-94cb-4f7d-afdf-d262ea0a95dc · outbound

This paper cites Referitgame: Referring to objects in photographs of natural scenes.

Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data Referitgame: Referring to objects in photographs of natural scenes

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:29:06.644003Z

Source-reported events for the cited work

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Observation b95a0afb-92f2-4760-a5f1-0ea9568eeeb5 · outbound

This paper cites Segment anything.

Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data Segment anything

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:29:06.366793Z

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 8953d258-6011-45cb-b50d-d91358910df8 · outbound

This paper cites Computer visualization of three-dimensional image data using imod.

Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data Computer visualization of three-dimensional image data using imod

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:29:06.116158Z

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 f05350a9-d2d8-46e3-bd06-4d4a7d7b2536 · outbound

This paper cites Understanding structure differences of irid- ium oxides depends on loading in proton exchange membrane electrolyzers.

Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data Understanding structure differences of irid- ium oxides depends on loading in proton exchange membrane electrolyzers

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:29:05.850739Z

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 e042354b-06c7-492a-82cf-001e1b627a40 · outbound

This paper cites Brickdl: Graph- level optimizations for dnns with fine-grained data blocking on gpus.

Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data Brickdl: Graph- level optimizations for dnns with fine-grained data blocking on gpus

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:29:05.594529Z

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 86b8710e-b5e9-4197-b8c3-20fba41e559c · outbound

This paper cites Grounding dino: Mar- rying dino with grounded pre-training for open-set object detection.

Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data Grounding dino: Mar- rying dino with grounded pre-training for open-set object detection

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:29:05.402858Z

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 9392f639-09cf-4a10-bd04-f01252889e86 · outbound

This paper cites Image Segmentation Using Text and Image Prompts.

Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data Image Segmentation Using Text and Image Prompts

Reference 17

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Source-reported events for the cited work

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Observation 01a7f6ae-ea98-40cf-9ab0-a80f451e19fa · outbound

This paper cites Segment anything in medical images.

Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data Segment anything in medical images

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:29:05.073493Z

Source-reported events for the cited work

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Observation 834ac26f-f99e-4939-b516-9a536870b966 · outbound

This paper cites Mazurowski, Haoyu Dong, Han Gu, Jichen Yang, Nicholas Saha, and Jiarui Luo.

Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data Mazurowski, Haoyu Dong, Han Gu, Jichen Yang, Nicholas Saha, and Jiarui Luo

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:29:04.772444Z

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 d388b154-e88b-4acd-beed-9ecc58d642ca · outbound

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

Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data SAM 2: Segment Anything in Images and Videos

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T21:29:01.664181Z

Source-reported events for the cited work

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Observation 30d7973c-0f65-41d5-b47b-af3ea64f52ca · outbound

This paper cites Grounded SAM: Assembling Open-World Models for Diverse Visual Tasks.

Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data Grounded SAM: Assembling Open-World Models for Diverse Visual Tasks

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T21:29:01.771327Z

Source-reported events for the cited work

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Observation 8432514c-eadf-4237-a71e-8192915d25e2 · outbound

This paper cites Nih image to imagej: 25 years of image analysis.

Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data Nih image to imagej: 25 years of image analysis

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:29:04.502178Z

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 41499b59-b191-4e22-bd75-87a36ad1f361 · outbound

This paper cites Parameter-Efficient Quantized Mixture-of-Experts Meets Vision-Language Instruction Tuning for Semiconductor Electron Micrograph Analysis.

Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data Parameter-Efficient Quantized Mixture-of-Experts Meets Vision-Language Instruction Tuning for Semiconductor Electron Micrograph Analysis

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-08-06T21:29:03.380734Z

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 b78cd9ae-7095-4ffc-8809-6924e1d0a0ea · outbound

This paper cites Interactive medical image segmentation using deep learning with image-specific fine tuning.

Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data Interactive medical image segmentation using deep learning with image-specific fine tuning

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:29:04.228755Z

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 545e7e6c-922f-4132-ba0c-71dcfb0af567 · outbound

This paper cites Deepigeos: a deep interactive geodesic frame- work for medical image segmentation.

Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data Deepigeos: a deep interactive geodesic frame- work for medical image segmentation

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:29:03.995113Z

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 dd378ec7-0537-45de-9032-ef3c027ed0cd · outbound

This paper cites Ushizima, Victor C.

Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data Ushizima, Victor C

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:29:03.703917Z

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 24d08a7b-0c8a-4350-b8b4-dc015fc8d815 · outbound

This paper cites Faster Segment Anything: Towards Lightweight SAM for Mobile Applications.

Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data Faster Segment Anything: Towards Lightweight SAM for Mobile Applications

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T21:29:02.487156Z

Source-reported events for the cited work

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Observation e365f2fe-1e37-435c-bb81-dfbd1172a0c6 · outbound

This paper cites Fast Segment Anything.

Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data Fast Segment Anything

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T21:29:02.654117Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3373b54d-4c69-4c27-88d2-2c97151db7ae · outbound

This paper cites MedUHIP: Towards Human-In-the-Loop Medical Segmentation.

Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data MedUHIP: Towards Human-In-the-Loop Medical Segmentation

Reference 29

Resolution: verified exact; local_arxiv, observed 2026-08-06T21:29:03.151969Z

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.

Pith citing papers

Observation f953fd77-f3ba-4424-8869-42674750db9f · inbound

Delivering Science as a Service: Sci-Orchestra's Cloud-Native Approach to HPC cites this paper.

Delivering Science as a Service: Sci-Orchestra's Cloud-Native Approach to HPC Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-12T08:06:29.328354Z

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.