Paper Citation Record · LEDGER

Dataset Pruning: Reducing Training Data by Examining Generalization Influence

As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2205.09329.

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

pith.paper-citation-record.v1
2205.09329 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T22:32:17.849316Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T20:40:07.609687Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
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malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 5af602d4-11a0-4e8e-99fb-e88dfa57fc1e · inbound

SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation cites this paper.

SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation Dataset Pruning: Reducing Training Data by Examining Generalization Influence

Reference 168

Resolution: verified exact; arxiv_id, observed 2026-05-16T17:56:23.605564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation df5cb2ad-f2cc-43f7-9a4b-a007ba840dea · inbound

Surprisingly High Redundancy in Electronic Structure Data Across Materials Explained by Low Intrinsic Dimensionality cites this paper.

Surprisingly High Redundancy in Electronic Structure Data Across Materials Explained by Low Intrinsic Dimensionality Dataset Pruning: Reducing Training Data by Examining Generalization Influence

Reference 74

Resolution: verified exact; arxiv_id, observed 2026-05-19T04:42:58.708905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 6bad427f-3841-44f5-adf0-b9a80d7127f9 · inbound

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models cites this paper.

MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models Dataset Pruning: Reducing Training Data by Examining Generalization Influence

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-04T22:32:17.849316Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d068dc37-bb0b-4770-84c9-ff61f9175b1c · inbound

Towards Multimodal Active Learning: Efficient Learning with Limited Paired Data cites this paper.

Towards Multimodal Active Learning: Efficient Learning with Limited Paired Data Dataset Pruning: Reducing Training Data by Examining Generalization Influence

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-18T13:21:23.867469Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation d859c6a1-2d00-492d-8768-0045a8ede3f6 · inbound

OPERA: Online Data Pruning for Efficient Retrieval Model Adaptation cites this paper.

OPERA: Online Data Pruning for Efficient Retrieval Model Adaptation Dataset Pruning: Reducing Training Data by Examining Generalization Influence

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-03T02:34:21.345501Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 88deb570-5f9d-4490-8764-cfefe56d70e9 · inbound

Adaptive Data Dropout: Towards Self-Regulated Learning in Deep Neural Networks cites this paper.

Adaptive Data Dropout: Towards Self-Regulated Learning in Deep Neural Networks Dataset Pruning: Reducing Training Data by Examining Generalization Influence

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-11T10:06:03.408797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 84a19e91-de4a-4ec0-8b46-c99377ef5dcd · inbound

Representation-Guided Parameter-Efficient LLM Unlearning cites this paper.

Representation-Guided Parameter-Efficient LLM Unlearning Dataset Pruning: Reducing Training Data by Examining Generalization Influence

Reference 140

Resolution: verified exact; arxiv_id, observed 2026-05-10T06:06:19.167225Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 91b0046e-0b63-4bcf-ba0c-75be0c970af0 · inbound

SLAP: Stratified Loss-based Pruning for On-Policy Data-Efficient Instruction Tuning cites this paper.

SLAP: Stratified Loss-based Pruning for On-Policy Data-Efficient Instruction Tuning Dataset Pruning: Reducing Training Data by Examining Generalization Influence

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-06-30T22:05:05.675799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 471f9fed-a8b5-4b85-bafc-938fed04291b · inbound

OrderDP: A Theoretically Guaranteed Lossless Dynamic Data Pruning Framework cites this paper.

OrderDP: A Theoretically Guaranteed Lossless Dynamic Data Pruning Framework Dataset Pruning: Reducing Training Data by Examining Generalization Influence

Reference 127

Resolution: verified exact; arxiv_id, observed 2026-07-02T23:07:27.179150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 56b5d1f3-6972-48fb-b2fb-3f289b6ef74b · inbound

Knowledge Cascade: Reverse Knowledge Distillation on Nonparametric Multivariate Functional Estimation cites this paper.

Knowledge Cascade: Reverse Knowledge Distillation on Nonparametric Multivariate Functional Estimation Dataset Pruning: Reducing Training Data by Examining Generalization Influence

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-07-04T20:40:07.611636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.