Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Pruning Neural Networks at Initialization: Why are We Missing the Mark?
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2009.08576.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T05:27:08.138617Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T08:19:44.449935Z
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 e34d31b1-8eba-4def-9c99-359ee05f01e3 · 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 Pruning Neural Networks at Initialization: Why are We Missing the Mark?
Reference 166
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T17:56:23.589568Z
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 7f676979-0471-4f67-8d53-952670ca7b16 · 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 Pruning Neural Networks at Initialization: Why are We Missing the Mark?
Reference 54
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T05:27:08.138617Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7a5d8efe-cdcd-4603-ba94-59321685c043 · inbound
Channel Location Constrains the Auditability of Subliminal Learning cites this paper.
Channel Location Constrains the Auditability of Subliminal Learning Pruning Neural Networks at Initialization: Why are We Missing the Mark?
Reference 25
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T08:19:44.451337Z
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.