Paper Citation Record · LEDGER

Comparing Rewinding and Fine-tuning in Neural Network Pruning

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2003.02389.

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

pith.paper-citation-record.v1
2003.02389 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T19:11:31.201754Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T21:16:13.442758Z

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 5aedab51-328b-44e2-af8e-3890c51c0b4f · inbound

TROI: Cross-Subject Pretraining with Sparse Voxel Selection for Enhanced fMRI Visual Decoding cites this paper.

TROI: Cross-Subject Pretraining with Sparse Voxel Selection for Enhanced fMRI Visual Decoding Comparing Rewinding and Fine-tuning in Neural Network Pruning

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-09T19:11:31.201754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 273b1061-f817-453b-bdec-47c13e36c41d · inbound

Accelerating Linear Recurrent Neural Networks for the Edge with Unstructured Sparsity cites this paper.

Accelerating Linear Recurrent Neural Networks for the Edge with Unstructured Sparsity Comparing Rewinding and Fine-tuning in Neural Network Pruning

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-09T15:48:57.381876Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5e2b20d2-4c34-4975-a31e-0d5f3d910e76 · inbound

STARFISH: faST Accuracy Recovery in pruned networks From Internal State Healing cites this paper.

STARFISH: faST Accuracy Recovery in pruned networks From Internal State Healing Comparing Rewinding and Fine-tuning in Neural Network Pruning

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-07-01T21:16:13.444797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e50026d6-7af9-4a74-9292-ddbaa2ec0eae · inbound

When AI Reviews Its Own Code: Recursive Self-Training Collapse in Code LLMs cites this paper.

When AI Reviews Its Own Code: Recursive Self-Training Collapse in Code LLMs Comparing Rewinding and Fine-tuning in Neural Network Pruning

Reference 104

Resolution: verified exact; arxiv_id, observed 2026-07-01T15:25:48.314176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.