Paper Citation Record · LEDGER

To Label or Not to Label: PALM -- A Predictive Model for Evaluating Sample Efficiency in Active Learning Models

As of 18 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2507.15381.

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

pith.paper-citation-record.v1
2507.15381 v1

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:39:24.081554Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

41 of 41 outbound references displayed

verified exact0
verified fuzzy29
unresolved11
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2e8f68d2-b111-46a6-ab91-2540e4f4db7f · outbound

This paper cites Active distance-based clustering using k- medoids.

To Label or Not to Label: PALM -- A Predictive Model for Evaluating Sample Efficiency in Active Learning Models Active distance-based clustering using k- medoids

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:24.527724Z

Source-reported events for the cited work

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Observation e51ed2c6-20ea-432d-b831-3ad3fc96fe85 · outbound

This paper cites Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds.

To Label or Not to Label: PALM -- A Predictive Model for Evaluating Sample Efficiency in Active Learning Models Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds

Reference 2

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Source-reported events for the cited work

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Observation 40d70092-e358-47b4-9dd5-81ff9b389a10 · outbound

This paper cites The power of ensembles for active learning in image classification.

To Label or Not to Label: PALM -- A Predictive Model for Evaluating Sample Efficiency in Active Learning Models The power of ensembles for active learning in image classification

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:24.518390Z

Source-reported events for the cited work

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Observation bc1ce61d-07be-4c9a-9d0e-1f06c2c14a88 · outbound

This paper cites Think twice before selection: Federated evidential active learning for medical image analysis with domain shifts.

To Label or Not to Label: PALM -- A Predictive Model for Evaluating Sample Efficiency in Active Learning Models Think twice before selection: Federated evidential active learning for medical image analysis with domain shifts

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:24.508775Z

Source-reported events for the cited work

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Observation c3a838f0-fb8e-4dcc-8409-cd5bae436995 · outbound

This paper cites A simple framework for contrastive learning of visual representations.

To Label or Not to Label: PALM -- A Predictive Model for Evaluating Sample Efficiency in Active Learning Models A simple framework for contrastive learning of visual representations

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:24.499419Z

Source-reported events for the cited work

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Observation 61654fe2-3c44-4bde-8a97-3dd1e709427c · outbound

This paper cites Improved Baselines with Momentum Contrastive Learning.

To Label or Not to Label: PALM -- A Predictive Model for Evaluating Sample Efficiency in Active Learning Models Improved Baselines with Momentum Contrastive Learning

Reference 6

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Source-reported events for the cited work

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Observation 300ccae6-d3a4-414a-b7b8-1ffeb053084c · outbound

This paper cites An empirical study of training self-supervised vision transformers.

To Label or Not to Label: PALM -- A Predictive Model for Evaluating Sample Efficiency in Active Learning Models An empirical study of training self-supervised vision transformers

Reference 7

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Source-reported events for the cited work

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Observation 0626ae5b-ef85-4dc4-88a0-ae5b41d1fbaa · outbound

This paper cites Class-balanced loss based on effective number of samples.

To Label or Not to Label: PALM -- A Predictive Model for Evaluating Sample Efficiency in Active Learning Models Class-balanced loss based on effective number of samples

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:24.483834Z

Source-reported events for the cited work

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Observation b5ebf464-0231-4df4-91a4-d4d5b0ffe79a · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

To Label or Not to Label: PALM -- A Predictive Model for Evaluating Sample Efficiency in Active Learning Models Imagenet: A large-scale hierarchical image database

Reference 9

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Source-reported events for the cited work

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Observation 3443bb0c-a4c6-4b00-88ae-31baafeb62c3 · outbound

This paper cites Deep bayesian active learning with image data.

To Label or Not to Label: PALM -- A Predictive Model for Evaluating Sample Efficiency in Active Learning Models Deep bayesian active learning with image data

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:24.468301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d6bcf64f-9167-442e-85bb-184b7770dba3 · outbound

This paper cites Discriminative Active Learning.

To Label or Not to Label: PALM -- A Predictive Model for Evaluating Sample Efficiency in Active Learning Models Discriminative Active Learning

Reference 11

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Source-reported events for the cited work

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Observation c6ff05b2-54ae-4aa6-a9db-e6d185d37c3a · outbound

This paper cites The Why, When, and How to Use Active Learning in Large-Data-Driven 3D Object Detection for Safe Autonomous Driving: An Empirical Exploration.

To Label or Not to Label: PALM -- A Predictive Model for Evaluating Sample Efficiency in Active Learning Models The Why, When, and How to Use Active Learning in Large-Data-Driven 3D Object Detection for Safe Autonomous Driving: An Empirical Exploration

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T15:39:23.995923Z

Source-reported events for the cited work

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Observation 81eaa379-5261-4df1-b0b2-40d22b1043f1 · outbound

This paper cites Bootstrap your own latent-a new approach to self-supervised learning.

To Label or Not to Label: PALM -- A Predictive Model for Evaluating Sample Efficiency in Active Learning Models Bootstrap your own latent-a new approach to self-supervised learning

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:24.458727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 15acf4c6-acac-44e0-adb9-2327dce639b5 · outbound

This paper cites Active Learning on a Budget: Opposite Strategies Suit High and Low Budgets.

To Label or Not to Label: PALM -- A Predictive Model for Evaluating Sample Efficiency in Active Learning Models Active Learning on a Budget: Opposite Strategies Suit High and Low Budgets

Reference 14

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Source-reported events for the cited work

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Observation 14977096-ad50-4917-a4a2-4775675d98c0 · outbound

This paper cites Deep residual learning for image recognition.

To Label or Not to Label: PALM -- A Predictive Model for Evaluating Sample Efficiency in Active Learning Models Deep residual learning for image recognition

Reference 15

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Source-reported events for the cited work

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Observation 79605fd4-a8bb-4434-a23e-59d9baee1da5 · outbound

This paper cites Off to a good start: Using clustering to select the initial training set in active learning.

To Label or Not to Label: PALM -- A Predictive Model for Evaluating Sample Efficiency in Active Learning Models Off to a good start: Using clustering to select the initial training set in active learning

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:24.443636Z

Source-reported events for the cited work

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Observation af95286d-7c27-4a2d-a7e2-bd718636778c · outbound

This paper cites Random coverings in several dimensions.

To Label or Not to Label: PALM -- A Predictive Model for Evaluating Sample Efficiency in Active Learning Models Random coverings in several dimensions

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:24.434846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6108c77f-05dc-4d2d-b2a4-beb13f53e6cb · outbound

This paper cites One- shot active learning for image segmentation via contrastive learning and diversity-based sampling.

To Label or Not to Label: PALM -- A Predictive Model for Evaluating Sample Efficiency in Active Learning Models One- shot active learning for image segmentation via contrastive learning and diversity-based sampling

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:24.426322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4d47fad0-fc7c-4a9c-bb65-4b804d233d43 · outbound

This paper cites Query- by-committee improvement with diversity and density in batch active learning.

To Label or Not to Label: PALM -- A Predictive Model for Evaluating Sample Efficiency in Active Learning Models Query- by-committee improvement with diversity and density in batch active learning

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:24.417356Z

Source-reported events for the cited work

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Observation e13aa215-e0bc-4ccc-a1ce-0bf7631db21c · outbound

This paper cites Learning multiple layers of features from tiny images, 2009.

To Label or Not to Label: PALM -- A Predictive Model for Evaluating Sample Efficiency in Active Learning Models Learning multiple layers of features from tiny images, 2009

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:24.407659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation cc4ad8c6-b534-400c-af91-00869b2e0b07 · outbound

This paper cites A sequential algorithm for training text clas- sifiers: Corrigendum and additional data.

To Label or Not to Label: PALM -- A Predictive Model for Evaluating Sample Efficiency in Active Learning Models A sequential algorithm for training text clas- sifiers: Corrigendum and additional data

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:24.398910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1060f357-d648-4416-b6db-4a760d921999 · outbound

This paper cites Semantic segmentation active learning with scene coverage coreset.

To Label or Not to Label: PALM -- A Predictive Model for Evaluating Sample Efficiency in Active Learning Models Semantic segmentation active learning with scene coverage coreset

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:24.389834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e72bf988-e23b-4b52-a87d-b174897cdc1b · outbound

This paper cites Exploring diversity- based active learning for 3d object detection in autonomous driving.

To Label or Not to Label: PALM -- A Predictive Model for Evaluating Sample Efficiency in Active Learning Models Exploring diversity- based active learning for 3d object detection in autonomous driving

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:24.380771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b28853ce-b4f8-4df4-9f98-e7596365f276 · outbound

This paper cites A unified approach to coreset learning.

To Label or Not to Label: PALM -- A Predictive Model for Evaluating Sample Efficiency in Active Learning Models A unified approach to coreset learning

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:24.370885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f25a1cb5-833e-4b3a-96f7-7b8d430f1877 · outbound

This paper cites Dcom: Active learning for all learners.

To Label or Not to Label: PALM -- A Predictive Model for Evaluating Sample Efficiency in Active Learning Models Dcom: Active learning for all learners

Reference 25

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Source-reported events for the cited work

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Observation 5877a40b-8599-4ebd-824f-6005387a42be · outbound

This paper cites Realistic evaluation of deep active learn- ing for image classification and semantic segmentation.

To Label or Not to Label: PALM -- A Predictive Model for Evaluating Sample Efficiency in Active Learning Models Realistic evaluation of deep active learn- ing for image classification and semantic segmentation

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:24.361608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e7784b7f-08a1-4c73-8139-4e054647dcba · outbound

This paper cites Towards robust and reproducible active learning using neural networks.

To Label or Not to Label: PALM -- A Predictive Model for Evaluating Sample Efficiency in Active Learning Models Towards robust and reproducible active learning using neural networks

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:24.352954Z

Source-reported events for the cited work

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Observation ab5f9b90-8979-43af-a9ff-817db2dd13b2 · outbound

This paper cites How to measure uncertainty in uncertainty sampling for active learning.

To Label or Not to Label: PALM -- A Predictive Model for Evaluating Sample Efficiency in Active Learning Models How to measure uncertainty in uncertainty sampling for active learning

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:24.344554Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0f73ef77-0f98-4354-9d0d-1d80d53acbcf · outbound

This paper cites Introduction to probability models.

To Label or Not to Label: PALM -- A Predictive Model for Evaluating Sample Efficiency in Active Learning Models Introduction to probability models

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f0bb5030-5ac1-409b-bcbe-fb54a6921b09 · outbound

This paper cites Active hidden markov models for information extraction.

To Label or Not to Label: PALM -- A Predictive Model for Evaluating Sample Efficiency in Active Learning Models Active hidden markov models for information extraction

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:24.326512Z

Source-reported events for the cited work

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Observation d1ed2cb8-9d72-48d8-b345-faa757509b28 · outbound

This paper cites Active Learning for Convolutional Neural Networks: A Core-Set Approach.

To Label or Not to Label: PALM -- A Predictive Model for Evaluating Sample Efficiency in Active Learning Models Active Learning for Convolutional Neural Networks: A Core-Set Approach

Reference 31

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Source-reported events for the cited work

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Observation eeee9024-d304-4e1a-a2ed-d8920c9122bb · outbound

This paper cites Active learning literature survey.

To Label or Not to Label: PALM -- A Predictive Model for Evaluating Sample Efficiency in Active Learning Models Active learning literature survey

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:24.317929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c2860db8-f10e-43ba-87c6-a94733cb6c07 · outbound

This paper cites Scan: Learning to classify images without labels.

To Label or Not to Label: PALM -- A Predictive Model for Evaluating Sample Efficiency in Active Learning Models Scan: Learning to classify images without labels

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:24.309322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation faa3c9e4-3c68-45fc-873e-f4dfc84ac607 · outbound

This paper cites Active clustering of biological sequences.

To Label or Not to Label: PALM -- A Predictive Model for Evaluating Sample Efficiency in Active Learning Models Active clustering of biological sequences

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:24.299185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation eb4baaf0-8850-4e8c-b32e-3e35cbbd177e · outbound

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

To Label or Not to Label: PALM -- A Predictive Model for Evaluating Sample Efficiency in Active Learning Models A comprehensive survey on deep active learning in medical image analysis

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:24.289332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a9627345-1322-4346-a3fb-9aeec0f7c477 · outbound

This paper cites Active trans- fer learning for 3d hippocampus segmentation.

To Label or Not to Label: PALM -- A Predictive Model for Evaluating Sample Efficiency in Active Learning Models Active trans- fer learning for 3d hippocampus segmentation

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:24.279403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation fb9a899a-a1d5-46ff-91a4-40dac0c2d1b9 · outbound

This paper cites Representative sampling for text classification using support vector machines.

To Label or Not to Label: PALM -- A Predictive Model for Evaluating Sample Efficiency in Active Learning Models Representative sampling for text classification using support vector machines

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:24.269042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 89ecb11e-c724-4c21-8ad9-4ec6f216adc9 · outbound

This paper cites Active learning through a covering lens.

To Label or Not to Label: PALM -- A Predictive Model for Evaluating Sample Efficiency in Active Learning Models Active learning through a covering lens

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:24.259365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ad5bf968-0f15-476c-85dd-cb3fbd5efb89 · outbound

This paper cites Anomaly detection for iot systems using active learning.

To Label or Not to Label: PALM -- A Predictive Model for Evaluating Sample Efficiency in Active Learning Models Anomaly detection for iot systems using active learning

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:39:24.249475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7e5e6f8e-c09b-4df8-909c-eb08c9507f76 · outbound

This paper cites LabelBench: A Comprehensive Framework for Benchmarking Adaptive Label-Efficient Learning.

To Label or Not to Label: PALM -- A Predictive Model for Evaluating Sample Efficiency in Active Learning Models LabelBench: A Comprehensive Framework for Benchmarking Adaptive Label-Efficient Learning

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-06T15:39:24.078500Z

Source-reported events for the cited work

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Observation 0e8a6fe4-a35d-4f57-9787-0871a94d140e · outbound

This paper cites BADGE [2] combines un- certainty and diversity by clustering in gradient space us- ing a k-means++ scheme.

To Label or Not to Label: PALM -- A Predictive Model for Evaluating Sample Efficiency in Active Learning Models BADGE [2] combines un- certainty and diversity by clustering in gradient space us- ing a k-means++ scheme

Reference 41

Resolution: malformed identifier; raw_fallback, observed 2026-08-06T15:39:24.239222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Pith citing papers

No inbound Pith citation observations are available.