Paper Citation Record · LEDGER

Active few-shot segmentation by reinforcing data selection

As of 4 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 0 inbound Pith citation observations for arXiv:2607.22371.

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

pith.paper-citation-record.v1
2607.22371 v1

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T05:01:36.623877Z

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+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

27 of 27 outbound references displayed

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verified fuzzy0
unresolved27
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 02149d02-25ff-43a4-a63d-53a76993c5e7 · outbound

This paper cites U-net: Convolu- tional networks for biomedical image segmentation.

Active few-shot segmentation by reinforcing data selection U-net: Convolu- tional networks for biomedical image segmentation

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-01T05:01:36.501340Z

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Unavailable: canonical work link unavailable.

Observation d88de284-ad75-406d-a3ee-b580e4758791 · outbound

This paper cites Medical image segmentation: A comprehensive review of deep learning-based methods.

Active few-shot segmentation by reinforcing data selection Medical image segmentation: A comprehensive review of deep learning-based methods

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-01T05:01:36.506609Z

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Observation 10e17f89-c83e-4e19-93e1-81470801f417 · outbound

This paper cites A review of artificial intelligence in prostate cancerdetectiononimaging.

Active few-shot segmentation by reinforcing data selection A review of artificial intelligence in prostate cancerdetectiononimaging

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-01T05:01:36.511259Z

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Observation 56909e4f-0b4d-4305-8546-941650cf34fc · outbound

This paper cites Medical image segmentation with limited su- pervision: a review of deep network models.

Active few-shot segmentation by reinforcing data selection Medical image segmentation with limited su- pervision: a review of deep network models

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-01T05:01:36.515921Z

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Observation 130c6292-34de-42b8-9bd7-c296f73857ba · outbound

This paper cites Active learning using adaptable task-based priori- tisation.

Active few-shot segmentation by reinforcing data selection Active learning using adaptable task-based priori- tisation

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-01T05:01:36.520522Z

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Observation 574227ab-aca4-4011-ba85-a1c91230d141 · outbound

This paper cites Issegmentationuncertaintyuseful?.

Active few-shot segmentation by reinforcing data selection Issegmentationuncertaintyuseful?

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-01T05:01:36.525186Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ed3aa827-7196-4510-8e80-26ee87c5b897 · outbound

This paper cites Development and evaluation of intraoperative ultrasound segmentation with negative image frames and multiple observer labels.

Active few-shot segmentation by reinforcing data selection Development and evaluation of intraoperative ultrasound segmentation with negative image frames and multiple observer labels

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-01T05:01:36.530549Z

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Observation 701e18eb-f629-409e-8928-fe0ec5591986 · outbound

This paper cites Embracing imperfect datasets: A review of deep learningsolutionsformedicalimagesegmentation.

Active few-shot segmentation by reinforcing data selection Embracing imperfect datasets: A review of deep learningsolutionsformedicalimagesegmentation

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-01T05:01:36.534986Z

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Observation 347cca59-a834-43eb-99e0-f926b138bb85 · outbound

This paper cites A systematic review of few-shot learn- ing in medical imaging.

Active few-shot segmentation by reinforcing data selection A systematic review of few-shot learn- ing in medical imaging

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-01T05:01:36.539184Z

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Observation b36bfb03-6387-4592-8d88-18fa41cccd20 · outbound

This paper cites Reasoning in machine vision by learning fast and slow thinking.

Active few-shot segmentation by reinforcing data selection Reasoning in machine vision by learning fast and slow thinking

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-01T05:01:36.543376Z

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Observation b7c00a20-3c36-4090-b280-18578c1da86c · outbound

This paper cites Model-agnostic meta- learning for fast adaptation of deep networks.

Active few-shot segmentation by reinforcing data selection Model-agnostic meta- learning for fast adaptation of deep networks

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-01T05:01:36.547642Z

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Observation 9d949aa6-dc4e-46c6-b8fd-314fefd82bc0 · outbound

This paper cites On First-Order Meta-Learning Algorithms.

Active few-shot segmentation by reinforcing data selection On First-Order Meta-Learning Algorithms

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-01T05:01:36.552168Z

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Observation e2439b58-e0c2-4820-9665-6833e00f6f4e · outbound

This paper cites Meta-learning with implicit gradients in a few- shot setting for medical image segmentation.

Active few-shot segmentation by reinforcing data selection Meta-learning with implicit gradients in a few- shot setting for medical image segmentation

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-01T05:01:36.556878Z

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Observation 59a8691f-c9be-4264-9960-83e8d3b5fc16 · outbound

This paper cites Few-shot learning for medical image segmentation using 3d u-net and model-agnostic meta-learning (maml).

Active few-shot segmentation by reinforcing data selection Few-shot learning for medical image segmentation using 3d u-net and model-agnostic meta-learning (maml)

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-01T05:01:36.561616Z

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Observation 4d63e4a0-2056-40e3-a9a6-d6bc777da645 · outbound

This paper cites Prototypical few-shot segmentation for cross-institution male pelvic structures with spatial registration.

Active few-shot segmentation by reinforcing data selection Prototypical few-shot segmentation for cross-institution male pelvic structures with spatial registration

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-01T05:01:36.566123Z

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Observation 1caf58d6-cb92-4749-a3c9-1956059a4d09 · outbound

This paper cites Few-shot medical image segmentation with high-fidelity prototypes.

Active few-shot segmentation by reinforcing data selection Few-shot medical image segmentation with high-fidelity prototypes

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-01T05:01:36.570762Z

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Observation 6ad42515-2630-4ada-bb0b-a13ca0bd1fd6 · outbound

This paper cites Variability and reproducibility in deep learning for medical image segmentation.

Active few-shot segmentation by reinforcing data selection Variability and reproducibility in deep learning for medical image segmentation

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-01T05:01:36.575828Z

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Observation 218ad090-f58c-4ba4-8999-5633ac18c8b5 · outbound

This paper cites A comprehensive survey on deep active learning in medical image analysis.

Active few-shot segmentation by reinforcing data selection A comprehensive survey on deep active learning in medical image analysis

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-01T05:01:36.580381Z

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Observation 7218265c-7b7f-4f6e-9d07-baf17ed07fda · outbound

This paper cites A survey on deep active learning: Recent advances and new frontiers.

Active few-shot segmentation by reinforcing data selection A survey on deep active learning: Recent advances and new frontiers

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-01T05:01:36.584699Z

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Observation fbd2f128-656e-490f-b8a1-7f4daa50d5a2 · outbound

This paper cites Image quality assessment for machine learning tasks using meta-reinforcement learning.

Active few-shot segmentation by reinforcing data selection Image quality assessment for machine learning tasks using meta-reinforcement learning

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-01T05:01:36.589556Z

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Observation 1b5b45d3-9d6f-45e4-a6da-fd7fe13d7de0 · outbound

This paper cites Learning to Learn for Few-shot Continual Active Learning.

Active few-shot segmentation by reinforcing data selection Learning to Learn for Few-shot Continual Active Learning

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-01T05:01:36.594208Z

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Observation 66bf0a31-9ca4-4641-b649-c9dad06b085c · outbound

This paper cites Data valuation using re- inforcement learning.

Active few-shot segmentation by reinforcing data selection Data valuation using re- inforcement learning

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-01T05:01:36.599187Z

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Observation bb3142aa-b791-45a9-88a4-010f8397eef7 · outbound

This paper cites Labeled TrustSet Guided: Batch Active Learning with Reinforcement Learning.

Active few-shot segmentation by reinforcing data selection Labeled TrustSet Guided: Batch Active Learning with Reinforcement Learning

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-01T05:01:36.604126Z

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Observation 8ce42afa-e5e9-4eaa-8619-a69012bfdc98 · outbound

This paper cites Batchbald: Effi- cient and diverse batch acquisition for deep bayesian active learning.

Active few-shot segmentation by reinforcing data selection Batchbald: Effi- cient and diverse batch acquisition for deep bayesian active learning

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-01T05:01:36.608864Z

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Observation 8cac5d15-f354-4e89-bbe9-bfd633a11431 · outbound

This paper cites Solving Continual Combinatorial Selection via Deep Reinforcement Learning.

Active few-shot segmentation by reinforcing data selection Solving Continual Combinatorial Selection via Deep Reinforcement Learning

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-01T05:01:36.613869Z

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Observation 2f1967ea-1f4e-4b82-b93c-ae9afb058fb9 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Active few-shot segmentation by reinforcing data selection Proximal Policy Optimization Algorithms

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-01T05:01:36.619033Z

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Observation aa2b8f8c-bed7-45fd-99a3-26d976dd7333 · outbound

This paper cites Adaptable image quality assessment using meta- reinforcement learning of task amenability.

Active few-shot segmentation by reinforcing data selection Adaptable image quality assessment using meta- reinforcement learning of task amenability

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-01T05:01:36.623877Z

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Pith citing papers

No inbound Pith citation observations are available.