Paper Citation Record · LEDGER

Class-Proportional Coreset Selection for Difficulty-Separable Data

As of 8 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 1 inbound Pith citation observation for arXiv:2507.10904.

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

pith.paper-citation-record.v1
2507.10904 v2

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:25:16.687564Z

measured 46 of 46 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-13T05:24:51.424634Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

45 of 45 outbound references displayed

verified exact1
verified fuzzy32
unresolved11
parse uncertain1
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 01282f90-63cd-4a76-b81e-7a944ba732da · outbound

This paper cites Super-Samples from Kernel Herding.

Class-Proportional Coreset Selection for Difficulty-Separable Data Super-Samples from Kernel Herding

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T17:25:11.717514Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2fccad6a-8a27-4721-be9e-1d778ed67d9c · outbound

This paper cites What is Your Data Worth to GPT? LLM-Scale Data Valuation with Influence Functions.

Class-Proportional Coreset Selection for Difficulty-Separable Data What is Your Data Worth to GPT? LLM-Scale Data Valuation with Influence Functions

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T17:25:11.881362Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2aed149c-5801-4f4a-82a7-ef9d39df3bfa · outbound

This paper cites Bws: best window selection based on sample scores for data pruning across broad ranges.

Class-Proportional Coreset Selection for Difficulty-Separable Data Bws: best window selection based on sample scores for data pruning across broad ranges

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:17.520489Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 722352c4-0b04-472b-9435-d5f4e8085cae · outbound

This paper cites Network Traffic Flow Generator.

Class-Proportional Coreset Selection for Difficulty-Separable Data Network Traffic Flow Generator

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:17.505211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8d47e2a8-57f9-45bf-bd75-a2e83f170bee · outbound

This paper cites Selection via proxy: Efficient data se- lection for deep learning.

Class-Proportional Coreset Selection for Difficulty-Separable Data Selection via proxy: Efficient data se- lection for deep learning

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:17.472954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 088c9faa-23b9-4205-820d-006c9db83342 · outbound

This paper cites Re- marks on some nonparametric estimates of a density func- tion.

Class-Proportional Coreset Selection for Difficulty-Separable Data Re- marks on some nonparametric estimates of a density func- tion

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:17.457688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9ace9fc2-a06b-4a87-85de-6753e9454ea3 · outbound

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

Class-Proportional Coreset Selection for Difficulty-Separable Data Imagenet: A large-scale hierarchical image database

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:17.442032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 34b08466-cb4a-4d96-9628-b80c64cc9b96 · outbound

This paper cites Characterization of encrypted and vpn traffic using time-related.

Class-Proportional Coreset Selection for Difficulty-Separable Data Characterization of encrypted and vpn traffic using time-related

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:17.427286Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a64dac5b-e765-495b-b696-4c5f71938081 · outbound

This paper cites An empirical comparison of botnet detection meth- ods.

Class-Proportional Coreset Selection for Difficulty-Separable Data An empirical comparison of botnet detection meth- ods

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:17.412200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4f3a14fe-2356-4b66-8a83-19dfe7bee2ae · outbound

This paper cites Network Intrusion Detection based on LSTM and Feature Embedding.

Class-Proportional Coreset Selection for Difficulty-Separable Data Network Intrusion Detection based on LSTM and Feature Embedding

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-08-06T17:25:16.967554Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 498e3abc-9517-4aec-9581-bab00139ca1f · outbound

This paper cites Deep residual learning for image recognition.

Class-Proportional Coreset Selection for Difficulty-Separable Data Deep residual learning for image recognition

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T17:25:13.525852Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9f9aab6a-a9fc-4d35-9d12-88a7980d91f2 · outbound

This paper cites Evolution-aware variance (eva) coreset selection for medical image classification.

Class-Proportional Coreset Selection for Difficulty-Separable Data Evolution-aware variance (eva) coreset selection for medical image classification

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:17.387492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 793fa85a-9e9d-4e32-b632-fa16ede6508b · outbound

This paper cites To- wards a universal features set for iot botnet attacks detection.

Class-Proportional Coreset Selection for Difficulty-Separable Data To- wards a universal features set for iot botnet attacks detection

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:17.373694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4e0f084a-db15-47c6-99e1-db2b659414d4 · outbound

This paper cites In2Core: Leveraging Influence Functions for Coreset Selection in Instruction Finetuning of Large Language Models.

Class-Proportional Coreset Selection for Difficulty-Separable Data In2Core: Leveraging Influence Functions for Coreset Selection in Instruction Finetuning of Large Language Models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T17:25:14.011205Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1cfcb38b-6a55-4d2e-bfdf-7076dbcc8f4f · outbound

This paper cites Retrieve: Coreset selection for efficient and robust semi-supervised learning.

Class-Proportional Coreset Selection for Difficulty-Separable Data Retrieve: Coreset selection for efficient and robust semi-supervised learning

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:17.360135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c0ab5f00-56e2-4645-b5e1-410cbaab9591 · outbound

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

Class-Proportional Coreset Selection for Difficulty-Separable Data Learning multiple layers of features from tiny images

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:17.345942Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 13949092-f91e-41ef-935c-b160fc2d0a68 · outbound

This paper cites Coreset selection for object detection.

Class-Proportional Coreset Selection for Difficulty-Separable Data Coreset selection for object detection

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:17.330660Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 31936a13-bbc9-4703-aed1-14da67955c03 · outbound

This paper cites Divergence measures based on the shannon en- tropy.

Class-Proportional Coreset Selection for Difficulty-Separable Data Divergence measures based on the shannon en- tropy

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:17.316324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation aa07a9c3-af0f-4e93-afba-2b9cbc95a72a · outbound

This paper cites Less is More: High-value Data Selection for Visual Instruction Tuning.

Class-Proportional Coreset Selection for Difficulty-Separable Data Less is More: High-value Data Selection for Visual Instruction Tuning

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T17:25:14.871493Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0dffaf00-3342-4a39-bc41-692af0387a05 · outbound

This paper cites Decoupled Weight Decay Regularization.

Class-Proportional Coreset Selection for Difficulty-Separable Data Decoupled Weight Decay Regularization

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T17:25:14.962162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 509b0903-c13a-4c79-80b7-be266353262b · outbound

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

Class-Proportional Coreset Selection for Difficulty-Separable Data D2 Pruning: Message Passing for Balancing Diversity and Difficulty in Data Pruning

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T17:25:15.023726Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a6ed124a-3806-4bb8-abf4-0244ba4cb4e1 · outbound

This paper cites Unsw-nb15: a comprehensive data set for network intrusion detection systems (unsw-nb15 network data set).

Class-Proportional Coreset Selection for Difficulty-Separable Data Unsw-nb15: a comprehensive data set for network intrusion detection systems (unsw-nb15 network data set)

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:17.301729Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c8b8d184-a0e5-4aa3-bdf3-47455364be29 · outbound

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

Class-Proportional Coreset Selection for Difficulty-Separable Data Deep learning on a data diet: Finding important ex- amples early in training

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:17.287647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e8262d71-cbda-48c2-999c-ce9002c48018 · outbound

This paper cites Identifying mislabeled data using the area under the margin ranking.

Class-Proportional Coreset Selection for Difficulty-Separable Data Identifying mislabeled data using the area under the margin ranking

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:17.273483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e12f992e-f5f2-4a4a-974d-e66f6a9eb566 · outbound

This paper cites Detecting so- cial engineering scams while preserving user privacy in the digital era (proposal position paper).

Class-Proportional Coreset Selection for Difficulty-Separable Data Detecting so- cial engineering scams while preserving user privacy in the digital era (proposal position paper)

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:17.259604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0844176d-a4b6-4e2a-8386-44a5db0b5ed6 · outbound

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

Class-Proportional Coreset Selection for Difficulty-Separable Data Active Learning for Convolutional Neural Networks: A Core-Set Approach

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T17:25:15.377800Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d218b51-aeac-4da8-88ce-769da092608b · outbound

This paper cites Toward generating a new intrusion detection dataset and intrusion traffic characterization.

Class-Proportional Coreset Selection for Difficulty-Separable Data Toward generating a new intrusion detection dataset and intrusion traffic characterization

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:17.245176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2cd55d4d-c51b-41ca-b0e6-17482a95accb · outbound

This paper cites Beyond neural scaling laws: beat- ing power law scaling via data pruning.

Class-Proportional Coreset Selection for Difficulty-Separable Data Beyond neural scaling laws: beat- ing power law scaling via data pruning

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:17.230199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b17f4196-9350-4130-a634-8304223c5d52 · outbound

This paper cites An empirical study of example forgetting during deep neural network learning.

Class-Proportional Coreset Selection for Difficulty-Separable Data An empirical study of example forgetting during deep neural network learning

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:17.215888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f27a5114-2126-4260-b7cf-1d450f42d2fd · outbound

This paper cites Modeling and detecting internet censorship events.

Class-Proportional Coreset Selection for Difficulty-Separable Data Modeling and detecting internet censorship events

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:17.201261Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d2f1111f-26bc-42df-adbf-0ee2ddb22bc0 · outbound

This paper cites Terms of de- ception: Exposing obscured financial obligations in online agreements with deep learning.

Class-Proportional Coreset Selection for Difficulty-Separable Data Terms of de- ception: Exposing obscured financial obligations in online agreements with deep learning

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:17.186240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e26d9da8-f722-42af-95df-dcf2f32e9c34 · outbound

This paper cites Harmful terms and where to find them: Measuring and modeling unfavorable financial terms and conditions in shopping websites at scale.

Class-Proportional Coreset Selection for Difficulty-Separable Data Harmful terms and where to find them: Measuring and modeling unfavorable financial terms and conditions in shopping websites at scale

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:17.171165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e51d4475-6642-43d6-bcad-c05506a6fbc2 · outbound

This paper cites Resdnvit: A hybrid architecture for netflow-based attack detection using a residual dense network and vision trans- former.

Class-Proportional Coreset Selection for Difficulty-Separable Data Resdnvit: A hybrid architecture for netflow-based attack detection using a residual dense network and vision trans- former

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:17.155964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 031eb95e-0d13-4622-8e73-72aeebf42deb · outbound

This paper cites Herding dynamical weights to learn.

Class-Proportional Coreset Selection for Difficulty-Separable Data Herding dynamical weights to learn

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:17.141052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation bea76b64-afea-4e70-826e-b5e3baf675e8 · outbound

This paper cites LESS: Selecting Influential Data for Targeted Instruction Tuning.

Class-Proportional Coreset Selection for Difficulty-Separable Data LESS: Selecting Influential Data for Targeted Instruction Tuning

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-06T17:25:16.024557Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 13e0d5b9-5018-4dd3-872e-6c922230b16c · outbound

This paper cites Rethinking Data Selection at Scale: Random Selection is Almost All You Need.

Class-Proportional Coreset Selection for Difficulty-Separable Data Rethinking Data Selection at Scale: Random Selection is Almost All You Need

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-06T17:25:16.084391Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f94dd75-b104-49ee-a4d1-f33353f1cb26 · outbound

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

Class-Proportional Coreset Selection for Difficulty-Separable Data Moderate coreset: A universal method of data selection for real-world data-efficient deep learning

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:17.126112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5c6c0a67-2344-4c84-beaf-204c8dc1fb38 · outbound

This paper cites Medmnist clas- sification decathlon: A lightweight automl benchmark for medical image analysis.

Class-Proportional Coreset Selection for Difficulty-Separable Data Medmnist clas- sification decathlon: A lightweight automl benchmark for medical image analysis

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:17.109849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b8f2a540-be6a-48b7-9b02-48c9b850736a · outbound

This paper cites Analyzing and storing network in- trusion detection data using bayesian coresets: a preliminary study in offline and streaming settings.

Class-Proportional Coreset Selection for Difficulty-Separable Data Analyzing and storing network in- trusion detection data using bayesian coresets: a preliminary study in offline and streaming settings

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:17.091823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation abdc9e9d-d352-496e-b425-ca5cecde5649 · outbound

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

Class-Proportional Coreset Selection for Difficulty-Separable Data Spanning training progress: Temporal dual-depth scoring (tdds) for enhanced dataset pruning

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:17.074263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a7d6c558-8738-444f-9b73-1abd79e70a5f · outbound

This paper cites Bridging Data and Hardware Gap for Ef- ficient Machine Learning Model Scaling.

Class-Proportional Coreset Selection for Difficulty-Separable Data Bridging Data and Hardware Gap for Ef- ficient Machine Learning Model Scaling

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:17.057447Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation aff6f8af-b8bf-40d1-8ae9-82b3fb218a2f · outbound

This paper cites Coverage-centric coreset selection for high pruning rates.

Class-Proportional Coreset Selection for Difficulty-Separable Data Coverage-centric coreset selection for high pruning rates

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:17.039430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4affabb1-ab3a-4056-8f0e-7cfcc11d8d5b · outbound

This paper cites Learn to be efficient: Build structured sparsity in large lan- guage models.

Class-Proportional Coreset Selection for Difficulty-Separable Data Learn to be efficient: Build structured sparsity in large lan- guage models

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:17.023406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 911347f4-5130-48da-b1f7-2c5439adfc17 · outbound

This paper cites ELFS: Label-Free Coreset Selection with Proxy Training Dynamics.

Class-Proportional Coreset Selection for Difficulty-Separable Data ELFS: Label-Free Coreset Selection with Proxy Training Dynamics

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-06T17:25:16.687564Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4ba8b6b2-72d8-4a54-924e-487ba1f271c3 · outbound

This paper cites an unresolved cited work.

Class-Proportional Coreset Selection for Difficulty-Separable Data Unresolved cited work

Reference 2017

Resolution: parse uncertain; raw_fallback, observed 2026-08-06T17:25:17.489668Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Pith citing papers

Observation 1d8e469e-480d-4b1f-87ca-4cdbe19756ed · inbound

A Coreset Selection Framework with Ensemble Aggregation for Image Classification cites this paper.

A Coreset Selection Framework with Ensemble Aggregation for Image Classification Class-Proportional Coreset Selection for Difficulty-Separable Data

Reference 6

Resolution: unresolved; no resolver link, observed 2026-07-13T05:24:51.424634Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.