Paper Citation Record · LEDGER

Dynamic Model Pruning with Feedback

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2006.07253.

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

pith.paper-citation-record.v1
2006.07253 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:40:01.479454Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T03:35:21.063039Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
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 bce40895-0488-482b-acbd-aee01177f8df · inbound

Exploring Vision Neural Network Pruning via Screening Methodology cites this paper.

Exploring Vision Neural Network Pruning via Screening Methodology Dynamic Model Pruning with Feedback

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-05-23T03:35:21.065410Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation eeb14255-c24c-408c-8437-a2b1da53971e · inbound

You Don't Need All Attentions: Distributed Dynamic Fine-Tuning for Foundation Models cites this paper.

You Don't Need All Attentions: Distributed Dynamic Fine-Tuning for Foundation Models Dynamic Model Pruning with Feedback

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-16T12:40:01.479454Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a0153aa3-4d9d-4222-9c95-bc05c720369a · inbound

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum cites this paper.

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum Dynamic Model Pruning with Feedback

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T05:27:08.079959Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 317a45d5-0056-4dcd-ae9a-69be752dac3e · inbound

Long-Tailed Data Classification by Increasing and Decreasing Neurons During Training cites this paper.

Long-Tailed Data Classification by Increasing and Decreasing Neurons During Training Dynamic Model Pruning with Feedback

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T17:48:04.859430Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 657713f1-a30a-412c-9774-82892e18e2a5 · inbound

Resource-Efficient Automatic Software Vulnerability Assessment via Knowledge Distillation and Particle Swarm Optimization cites this paper.

Resource-Efficient Automatic Software Vulnerability Assessment via Knowledge Distillation and Particle Swarm Optimization Dynamic Model Pruning with Feedback

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T11:27:32.145656Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bad9b1ae-20a6-40f8-bad8-c0b9c8a53981 · inbound

Delta-SVD: Efficient Compression for Personalized Text-to-Image Models cites this paper.

Delta-SVD: Efficient Compression for Personalized Text-to-Image Models Dynamic Model Pruning with Feedback

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-05T17:14:00.364260Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cc3a75a6-2cab-4d53-a16e-f1d7a3c49565 · inbound

CAGE: Curvature-Aware Gradient Estimation For Accurate Quantization-Aware Training cites this paper.

CAGE: Curvature-Aware Gradient Estimation For Accurate Quantization-Aware Training Dynamic Model Pruning with Feedback

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-04T08:50:46.729246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 25eb551e-97e2-458b-acbb-547225225f2b · inbound

Compositional Zero-Shot Recognition based on Tangent Space Disentanglement for Composite Modulation Signals cites this paper.

Compositional Zero-Shot Recognition based on Tangent Space Disentanglement for Composite Modulation Signals Dynamic Model Pruning with Feedback

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-02T05:10:53.893242Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.