Paper Citation Record · LEDGER

Trust-Aware Diversion for Data-Effective Distillation

As of 9 August 2026, this Paper Citation Record lists 61 of 61 outbound references and 1 inbound Pith citation observation for arXiv:2502.05027.

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

pith.paper-citation-record.v1
2502.05027 v1

Coverage vector

measured 61 of 61 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T20:38:26.368749Z

measured 62 of 62 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 2026-08-08T18:29:50.919240Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-08T18:29:51.364501Z

Reference resolution

61 of 61 outbound references displayed

verified exact0
verified fuzzy42
unresolved19
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c90c34cd-9e96-4586-9ef3-960fd71332e1 · outbound

This paper cites write newline.

Trust-Aware Diversion for Data-Effective Distillation write newline

Reference 1

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Observation 8b432889-d20f-4f31-a22a-88c5f6e46216 · outbound

This paper cites E., and McGuinness, K.

Trust-Aware Diversion for Data-Effective Distillation E., and McGuinness, K

Reference 2

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Observation ab0d1d7d-1d63-459e-9f6c-651435c28690 · outbound

This paper cites Unsupervised label noise modeling and loss correction.

Trust-Aware Diversion for Data-Effective Distillation Unsupervised label noise modeling and loss correction

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:38:28.094881Z

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Observation 7a3c5637-6398-4364-a9b8-fd6631524a93 · outbound

This paper cites S., Maharaj, T., Fischer, A., Courville, A., Bengio, Y., et al.

Trust-Aware Diversion for Data-Effective Distillation S., Maharaj, T., Fischer, A., Courville, A., Bengio, Y., et al

Reference 4

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Observation 8b9e47c2-affc-4a78-aa79-9666235305be · outbound

This paper cites A., and Zhu, J.-Y.

Trust-Aware Diversion for Data-Effective Distillation A., and Zhu, J.-Y

Reference 5

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Observation 47075749-cfa3-4c3c-97ff-cd0e7c35b272 · outbound

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

Trust-Aware Diversion for Data-Effective Distillation A simple framework for contrastive learning of visual representations

Reference 6

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Observation 62a82213-c8d7-4d5d-8ab1-b64ebadc4ddb · outbound

This paper cites Rethinking backdoor attacks on dataset distillation: A kernel method perspective.

Trust-Aware Diversion for Data-Effective Distillation Rethinking backdoor attacks on dataset distillation: A kernel method perspective

Reference 7

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Observation bbbbc34c-78b8-4af8-a898-1e0fb7514c53 · outbound

This paper cites Beyond mahalanobis distance for textual ood detection.

Trust-Aware Diversion for Data-Effective Distillation Beyond mahalanobis distance for textual ood detection

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:38:27.863598Z

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Observation 23d184de-bd90-4747-8268-4c1ed6f98c7e · outbound

This paper cites Dc-bench: Dataset condensation benchmark.

Trust-Aware Diversion for Data-Effective Distillation Dc-bench: Dataset condensation benchmark

Reference 9

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Observation ca70b510-c174-4e5b-b4ad-1d5951d6e42e · outbound

This paper cites an unresolved cited work.

Trust-Aware Diversion for Data-Effective Distillation Unresolved cited work

Reference 10

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Observation 57d36381-1050-45fd-ba3c-7ca1a27d770b · outbound

This paper cites Exploiting inter-sample and inter-feature relations in dataset distillation.

Trust-Aware Diversion for Data-Effective Distillation Exploiting inter-sample and inter-feature relations in dataset distillation

Reference 11

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Observation 21b4f2cf-5339-4534-9577-dbcd14e21a1f · outbound

This paper cites Y., Zhou, J.

Trust-Aware Diversion for Data-Effective Distillation Y., Zhou, J

Reference 12

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Observation 05c923c4-c5eb-4dc7-8c07-cfd6cb92bce6 · outbound

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Trust-Aware Diversion for Data-Effective Distillation Unresolved cited work

Reference 13

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Observation 3e4db83d-80bd-4670-867a-a5964b7623b4 · outbound

This paper cites Fecam: Exploiting the heterogeneity of class distributions in exemplar-free continual learning.

Trust-Aware Diversion for Data-Effective Distillation Fecam: Exploiting the heterogeneity of class distributions in exemplar-free continual learning

Reference 14

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Observation 6d3d6755-c6ff-4128-8be9-06fa215119b2 · outbound

This paper cites Summarizing stream data for memory-restricted online continual learning.

Trust-Aware Diversion for Data-Effective Distillation Summarizing stream data for memory-restricted online continual learning

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:38:27.749671Z

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Observation 9aff4e70-5c31-4671-900b-298486153d51 · outbound

This paper cites Towards lossless dataset distillation via difficulty-aligned trajectory matching.

Trust-Aware Diversion for Data-Effective Distillation Towards lossless dataset distillation via difficulty-aligned trajectory matching

Reference 16

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Observation 79a18634-8781-49ed-a9cf-b50ecb67f5fb · outbound

This paper cites Co-teaching: Robust training of deep neural networks with extremely noisy labels.

Trust-Aware Diversion for Data-Effective Distillation Co-teaching: Robust training of deep neural networks with extremely noisy labels

Reference 17

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Observation fa6c3976-55c7-4043-8323-d341c86b9ed3 · outbound

This paper cites Deep residual learning for image recognition.

Trust-Aware Diversion for Data-Effective Distillation Deep residual learning for image recognition

Reference 18

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Observation 8a7c8d75-4114-491f-a1df-f17f4ce9ddb3 · outbound

This paper cites Momentum contrast for unsupervised visual representation learning.

Trust-Aware Diversion for Data-Effective Distillation Momentum contrast for unsupervised visual representation learning

Reference 19

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Observation 5cc50547-c388-4885-b502-bc56159669f1 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Trust-Aware Diversion for Data-Effective Distillation Distilling the Knowledge in a Neural Network

Reference 20

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Observation 5f40d8b3-026f-4edd-b22e-89544fa84a42 · outbound

This paper cites N., Rahnavard, N., Mian, A., and Shah, M.

Trust-Aware Diversion for Data-Effective Distillation N., Rahnavard, N., Mian, A., and Shah, M

Reference 21

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Observation 3fc8fd8c-129d-42bf-bb0f-0df23dad84a4 · outbound

This paper cites J., Yun, S., Song, H., Jeong, J., Ha, J.-W., and Song, H.

Trust-Aware Diversion for Data-Effective Distillation J., Yun, S., Song, H., Jeong, J., Ha, J.-W., and Song, H

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:38:27.600290Z

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Observation 1ef7622f-efca-4aad-b81a-c843819d6e41 · outbound

This paper cites Dataset condensation with contrastive signals.

Trust-Aware Diversion for Data-Effective Distillation Dataset condensation with contrastive signals

Reference 23

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Observation d7f403c6-a4ea-4643-8979-7d9cd244b939 · outbound

This paper cites Dataset distillation for medical dataset sharing.

Trust-Aware Diversion for Data-Effective Distillation Dataset distillation for medical dataset sharing

Reference 24

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Observation e28c7809-e548-42f0-8e90-6cb9b8f92736 · outbound

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Trust-Aware Diversion for Data-Effective Distillation Unresolved cited work

Reference 25

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Observation ef702e17-238f-403e-86fa-9d8db8c74fcc · outbound

This paper cites Neighborhood collective estimation for noisy label identification and correction.

Trust-Aware Diversion for Data-Effective Distillation Neighborhood collective estimation for noisy label identification and correction

Reference 26

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Observation 773e0a96-22a9-4ec4-8fe5-a4635fd90476 · outbound

This paper cites and Kainz, B.

Trust-Aware Diversion for Data-Effective Distillation and Kainz, B

Reference 27

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Observation 830e90f1-06c2-4c9a-a74a-86e421ca2efd · outbound

This paper cites Prioritize Alignment in Dataset Distillation.

Trust-Aware Diversion for Data-Effective Distillation Prioritize Alignment in Dataset Distillation

Reference 28

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Observation 166f5a8b-ef20-446c-81b1-984f756dbe37 · outbound

This paper cites Dataset distillation by automatic training trajectories.

Trust-Aware Diversion for Data-Effective Distillation Dataset distillation by automatic training trajectories

Reference 29

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Observation aea5dbb4-7a0d-4f15-8c3c-d3cd0c739247 · outbound

This paper cites Dataset Distillation via the Wasserstein Metric.

Trust-Aware Diversion for Data-Effective Distillation Dataset Distillation via the Wasserstein Metric

Reference 30

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Observation 9b1be0e8-32ca-4559-9ac4-23b73d52f01f · outbound

This paper cites Early-learning regularization prevents memorization of noisy labels.

Trust-Aware Diversion for Data-Effective Distillation Early-learning regularization prevents memorization of noisy labels

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:38:27.287173Z

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Observation 4b82a26f-0688-4ad6-b035-ec742c0e1905 · outbound

This paper cites and D'yakonov, A.

Trust-Aware Diversion for Data-Effective Distillation and D'yakonov, A

Reference 32

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Observation 4e0eb26b-ed0c-4f04-aff6-2eab35409523 · outbound

This paper cites Confident learning: Estimating uncertainty in dataset labels.

Trust-Aware Diversion for Data-Effective Distillation Confident learning: Estimating uncertainty in dataset labels

Reference 33

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Observation 86d364b6-67fe-4174-893d-a73650e7f5ea · outbound

This paper cites A label is worth a thousand images in dataset distillation.

Trust-Aware Diversion for Data-Effective Distillation A label is worth a thousand images in dataset distillation

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:38:27.231730Z

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Observation 3f85369b-798e-4669-8940-32169bc5b67b · outbound

This paper cites Z., Lawryshyn, Y.

Trust-Aware Diversion for Data-Effective Distillation Z., Lawryshyn, Y

Reference 35

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Observation 7df58d21-a4b3-44c1-b7f7-9e1112d6ec99 · outbound

This paper cites Sample condensation in online continual learning.

Trust-Aware Diversion for Data-Effective Distillation Sample condensation in online continual learning

Reference 36

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Observation 90b2c4f9-0056-4453-9344-965192b74686 · outbound

This paper cites Generalized large-scale data condensation via various backbone and statistical matching.

Trust-Aware Diversion for Data-Effective Distillation Generalized large-scale data condensation via various backbone and statistical matching

Reference 37

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Observation 6010ec55-8d79-4fdd-be63-f299e7af9f08 · outbound

This paper cites FYI : Flip your images for dataset distillation.

Trust-Aware Diversion for Data-Effective Distillation FYI : Flip your images for dataset distillation

Reference 38

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Observation f0f9d196-f3e9-44c4-bc90-9ce28af1921b · outbound

This paper cites and Schonlau, M.

Trust-Aware Diversion for Data-Effective Distillation and Schonlau, M

Reference 39

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Observation ab074138-330c-4d5c-90d3-58df62fe3d26 · outbound

This paper cites On the diversity and realism of distilled dataset: An efficient dataset distillation paradigm.

Trust-Aware Diversion for Data-Effective Distillation On the diversity and realism of distilled dataset: An efficient dataset distillation paradigm

Reference 40

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This paper cites Joint optimization framework for learning with noisy labels.

Trust-Aware Diversion for Data-Effective Distillation Joint optimization framework for learning with noisy labels

Reference 41

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Trust-Aware Diversion for Data-Effective Distillation Dataset Distillation

Reference 42

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This paper cites Combating noisy labels by agreement: A joint training method with co-regularization.

Trust-Aware Diversion for Data-Effective Distillation Combating noisy labels by agreement: A joint training method with co-regularization

Reference 43

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Observation f6a63a22-876b-4d90-8aa6-de93731ce30d · outbound

This paper cites Mitigating memorization of noisy labels by clipping the model prediction.

Trust-Aware Diversion for Data-Effective Distillation Mitigating memorization of noisy labels by clipping the model prediction

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:38:26.906442Z

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Observation 2ee4d7a6-6b1d-42fc-a803-4f84ab260cce · outbound

This paper cites Learning with noisy labels revisited: A study using real-world human annotations.

Trust-Aware Diversion for Data-Effective Distillation Learning with noisy labels revisited: A study using real-world human annotations

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:38:26.884741Z

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Observation ee12ca25-7c84-408c-a030-4f048f59560e · outbound

This paper cites Sparse parameterization for epitomic dataset distillation.

Trust-Aware Diversion for Data-Effective Distillation Sparse parameterization for epitomic dataset distillation

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:38:26.855124Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e9810919-6545-4119-a136-57543f551ff9 · outbound

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

Trust-Aware Diversion for Data-Effective Distillation Robust early-learning: Hindering the memorization of noisy labels

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:38:26.818426Z

Source-reported events for the cited work

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Observation 011bd63e-0966-4995-8638-81b9f7d0f399 · outbound

This paper cites and He, Y.

Trust-Aware Diversion for Data-Effective Distillation and He, Y

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:38:26.774739Z

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Observation 7a280ac0-1cfb-4cf6-9d9e-29e067fd6719 · outbound

This paper cites An efficient dataset condensation plugin and its application to continual learning.

Trust-Aware Diversion for Data-Effective Distillation An efficient dataset condensation plugin and its application to continual learning

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:38:26.724801Z

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Observation 569fa8c4-966c-4301-a7ac-ec6eff6d88d6 · outbound

This paper cites Learning with twin noisy labels for visible-infrared person re-identification.

Trust-Aware Diversion for Data-Effective Distillation Learning with twin noisy labels for visible-infrared person re-identification

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:38:26.699600Z

Source-reported events for the cited work

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Observation 096656de-2658-44f9-8933-4f2dabf6f020 · outbound

This paper cites Neural spectral decomposition for dataset distillation.

Trust-Aware Diversion for Data-Effective Distillation Neural spectral decomposition for dataset distillation

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:38:26.682983Z

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Observation eb6fcf9c-6067-404d-adf0-5e88ad22ac94 · outbound

This paper cites an unresolved cited work.

Trust-Aware Diversion for Data-Effective Distillation Unresolved cited work

Reference 52

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Observation 65f5eec2-62a5-47fe-a10b-7d26bf3fc121 · outbound

This paper cites and Wu, J.

Trust-Aware Diversion for Data-Effective Distillation and Wu, J

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:38:26.649845Z

Source-reported events for the cited work

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Observation 542451a6-02d1-4bef-afb3-24d9d4d02bea · outbound

This paper cites Squeeze, recover and relabel: Dataset condensation at imagenet scale from a new perspective.

Trust-Aware Diversion for Data-Effective Distillation Squeeze, recover and relabel: Dataset condensation at imagenet scale from a new perspective

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:38:26.634072Z

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 a54dffd7-76cb-4e7a-873e-9912d221c1fa · outbound

This paper cites and Bilen, H.

Trust-Aware Diversion for Data-Effective Distillation and Bilen, H

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:38:26.616680Z

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 7adb7073-94f4-4274-9fa2-bd17a8bfe0de · outbound

This paper cites and Bilen, H.

Trust-Aware Diversion for Data-Effective Distillation and Bilen, H

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:38:26.601187Z

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 d6b88391-8154-4c4a-bfba-64baed40a7c7 · outbound

This paper cites Centrality and consistency: two-stage clean samples identification for learning with instance-dependent noisy labels.

Trust-Aware Diversion for Data-Effective Distillation Centrality and consistency: two-stage clean samples identification for learning with instance-dependent noisy labels

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:38:26.585155Z

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 bb1b2b6a-138c-48cb-8c3a-a00ff2a58628 · outbound

This paper cites Improved distribution matching for dataset condensation.

Trust-Aware Diversion for Data-Effective Distillation Improved distribution matching for dataset condensation

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-08T20:38:26.354329Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f69cf846-9f3c-4003-a80f-6c3f4a7acde3 · outbound

This paper cites M., and Litany, O.

Trust-Aware Diversion for Data-Effective Distillation M., and Litany, O

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:38:26.558825Z

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 c1cb1f11-33d2-4ae8-8ed5-23016f319a4c · outbound

This paper cites Robust curriculum learning: from clean label detection to noisy label self-correction.

Trust-Aware Diversion for Data-Effective Distillation Robust curriculum learning: from clean label detection to noisy label self-correction

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:38:26.542671Z

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 f15896a3-5b61-43b2-8d8c-f56617423a6b · outbound

This paper cites P., and Xing, L.

Trust-Aware Diversion for Data-Effective Distillation P., and Xing, L

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:38:26.508733Z

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 62aacf60-8e33-4d2b-861b-f2a75da8696c · inbound

The Evolution of Dataset Distillation: Toward Scalable and Generalizable Solutions cites this paper.

The Evolution of Dataset Distillation: Toward Scalable and Generalizable Solutions Trust-Aware Diversion for Data-Effective Distillation

Reference 198

Resolution: verified exact; local_arxiv, observed 2026-08-08T18:29:51.369510Z

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.