Paper Citation Record · LEDGER

Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty

As of 9 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 3 inbound Pith citation observations for arXiv:2502.06905.

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

pith.paper-citation-record.v1
2502.06905 v3

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T16:55:17.645929Z

measured 36 of 36 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 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:53:07.138400Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

33 of 33 outbound references displayed

verified exact2
verified fuzzy14
unresolved16
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation ae97a2a0-ce68-46cd-a010-ad21b87eb178 · outbound

This paper cites Balancing feature similarity and label variability for optimal size-aware one-shot subset selection.

Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty Balancing feature similarity and label variability for optimal size-aware one-shot subset selection

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:55:18.221553Z

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 6688bee4-2a87-4e43-9e82-3750579a8cb1 · outbound

This paper cites A closer look at memorization in deep networks.

Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty A closer look at memorization in deep networks

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-08T16:55:17.366819Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ec42a330-5887-47c8-8333-83f03847486c · outbound

This paper cites Curriculum learning.

Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty Curriculum learning

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:55:18.208070Z

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 a8d67be4-8656-4de6-876f-e52c4ca5c7b3 · outbound

This paper cites BWS: Best Window Selection Based on Sample Scores for Data Pruning across Broad Ranges.

Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty BWS: Best Window Selection Based on Sample Scores for Data Pruning across Broad Ranges

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-08-08T16:55:17.910432Z

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 ea7bbfc4-ce2b-4519-9af4-e81a53b20f96 · outbound

This paper cites Selection via Proxy: Efficient Data Selection for Deep Learning.

Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty Selection via Proxy: Efficient Data Selection for Deep Learning

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-08T16:55:17.377215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6b533af0-7338-4f83-a301-198b0a2f33e3 · outbound

This paper cites Data and parameter scaling laws for neural machine translation.

Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty Data and parameter scaling laws for neural machine translation

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:55:18.179019Z

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 5dd54506-fe52-4ff4-896f-1d9ca9d19081 · outbound

This paper cites Implicit bias of gradient descent on linear convolutional networks.

Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty Implicit bias of gradient descent on linear convolutional networks

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-08T16:55:17.383760Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e295d1d5-d398-49f7-bf79-97edc110eb82 · outbound

This paper cites Deep Residual Learning for Image Recognition.

Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty Deep Residual Learning for Image Recognition

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-08T16:55:17.394225Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bbca8637-5aed-4083-9edc-5b50ec8b4e3a · outbound

This paper cites Large-scale dataset pruning with dynamic uncertainty.

Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty Large-scale dataset pruning with dynamic uncertainty

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:55:18.060834Z

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 c8517c7f-6656-4915-b59a-928225fb3fae · outbound

This paper cites Benchmarking Neural Network Robustness to Common Corruptions and Perturbations.

Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty Benchmarking Neural Network Robustness to Common Corruptions and Perturbations

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-08T16:55:17.481088Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 408e3ab7-8a19-4edf-ab4b-d9b9a5286547 · outbound

This paper cites Deep Learning Scaling is Predictable, Empirically.

Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty Deep Learning Scaling is Predictable, Empirically

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-08T16:55:17.515724Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5afd24d8-08a1-4103-bbaa-24a71293f9af · outbound

This paper cites Characterizing Structural Regularities of Labeled Data in Overparameterized Models.

Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty Characterizing Structural Regularities of Labeled Data in Overparameterized Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-08T16:55:17.550053Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 410238ff-de77-4e16-ae41-912814d4a138 · outbound

This paper cites Selective-supervised contrastive learning with noisy labels.

Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty Selective-supervised contrastive learning with noisy labels

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:55:18.033530Z

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 309275ea-fc1a-4b50-965b-2a509569bfed · outbound

This paper cites D2 Pruning: Message Passing for Balancing Diversity and Difficulty in Data Pruning.

Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty D2 Pruning: Message Passing for Balancing Diversity and Difficulty in Data Pruning

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-08T16:55:17.593167Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 62b2da2f-79d5-41fc-9017-3cdc1fdd7f0b · outbound

This paper cites Making deep neural networks robust to label noise: A loss correction approach.

Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty Making deep neural networks robust to label noise: A loss correction approach

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-08T16:55:17.596525Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 357f8c55-59b2-4a48-b226-7b9716cb7f9a · outbound

This paper cites Deep learning on a data diet: Finding important examples early in training.

Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty Deep learning on a data diet: Finding important examples early in training

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:55:18.018449Z

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 8ccd08fb-4637-4a0f-9d8c-ad9d79c1e04c · outbound

This paper cites Identifying Mislabeled Data using the Area Under the Margin Ranking.

Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty Identifying Mislabeled Data using the Area Under the Margin Ranking

Reference 17

Resolution: metadata mismatch; local_arxiv, observed 2026-08-08T16:55:17.794292Z

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 7e057948-83c4-4227-a09d-a08b528836e5 · outbound

This paper cites A Constructive Prediction of the Generalization Error Across Scales.

Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty A Constructive Prediction of the Generalization Error Across Scales

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-08T16:55:17.605900Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b2fba5a3-6d66-4435-9bb8-17db8f217349 · outbound

This paper cites Data augmentation as feature manipulation.

Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty Data augmentation as feature manipulation

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:55:18.009844Z

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 df5811ca-1075-43b6-9685-f31745942e30 · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-08T16:55:17.611938Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e3e46641-37fe-4e17-8ebf-33f83cf519d6 · outbound

This paper cites an unresolved cited work.

Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty Unresolved cited work

Reference 21

Resolution: unresolved; raw_fallback, observed 2026-08-08T16:55:18.000646Z

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 362d8f55-1c29-4c0d-b537-377b92babd67 · outbound

This paper cites The implicit bias of gradient descent on separable data.

Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty The implicit bias of gradient descent on separable data

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-08T16:55:17.617282Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 41008f06-d9e2-43b6-b602-fac6d89c0380 · outbound

This paper cites Dataset cartography: Mapping and diagnosing datasets with training dynamics.

Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty Dataset cartography: Mapping and diagnosing datasets with training dynamics

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:55:17.987003Z

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 5b246f73-cf9d-487f-ba1b-d7a6bf40cf52 · outbound

This paper cites Data pruning by information maximization.

Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty Data pruning by information maximization

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:55:17.978949Z

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 63eb6278-5b24-4c81-a187-45d6b1f3fcc6 · outbound

This paper cites An Empirical Study of Example Forgetting during Deep Neural Network Learning.

Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty An Empirical Study of Example Forgetting during Deep Neural Network Learning

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-08T16:55:17.623919Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4d0fb30d-b6db-48b3-8c97-7b5645f7dfc5 · outbound

This paper cites Iterative learning with open-set noisy labels.

Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty Iterative learning with open-set noisy labels

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:55:17.970065Z

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 4c75c90f-9c44-42ec-9b39-24314c2d6947 · outbound

This paper cites Robust early-learning: Hindering the memorization of noisy labels.

Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty Robust early-learning: Hindering the memorization of noisy labels

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:55:17.961592Z

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 b256e60f-81b7-4946-9496-fc89b97c94d3 · outbound

This paper cites Instance Correction for Learning with Open-set Noisy Labels.

Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty Instance Correction for Learning with Open-set Noisy Labels

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-08-08T16:55:17.709828Z

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 f4545963-911f-480d-9063-d6e1e5d1ba88 · outbound

This paper cites Moderate coreset: A universal method of data selection for real-world data-efficient deep learning.

Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty Moderate coreset: A universal method of data selection for real-world data-efficient deep learning

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:55:17.952478Z

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 b421b17d-451c-4c47-a9d5-5e19fcf114bb · outbound

This paper cites Mind the boundary: Coreset selection via reconstructing the decision boundary.

Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty Mind the boundary: Coreset selection via reconstructing the decision boundary

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:55:17.943248Z

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 4c2297bd-79f4-4dc8-927f-a27e503782f6 · outbound

This paper cites Spanning training progress: Temporal dual-depth scoring (tdds) for enhanced dataset pruning.

Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty Spanning training progress: Temporal dual-depth scoring (tdds) for enhanced dataset pruning

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:55:17.934211Z

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 29b8f116-d98c-4bf7-b498-a4294d758b08 · outbound

This paper cites Coverage-centric Coreset Selection for High Pruning Rates.

Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty Coverage-centric Coreset Selection for High Pruning Rates

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-08T16:55:17.642708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a4e2683d-6f20-4ad5-99cc-8c5295785f06 · outbound

This paper cites Probabilistic Bilevel Coreset Selection.

Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty Probabilistic Bilevel Coreset Selection

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-08T16:55:17.645929Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 58958b4e-c1ec-47d5-9215-fbeeec23e81b · inbound

Extending Dataset Pruning to Object Detection: A Variance-based Approach cites this paper.

Extending Dataset Pruning to Object Detection: A Variance-based Approach Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T14:53:07.138400Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 81cccf8e-54b2-4c00-8a7e-ee6f9d0e58aa · inbound

Model Parallelism With Subnetwork Data Parallelism cites this paper.

Model Parallelism With Subnetwork Data Parallelism Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T18:19:59.327333Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d798a7fd-1861-44c6-9365-0017a2752ceb · inbound

GRACE: A Dynamic Coreset Selection Framework for Large Language Model Optimization cites this paper.

GRACE: A Dynamic Coreset Selection Framework for Large Language Model Optimization Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-10T20:30:49.080101Z

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.