Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Pruning-as-Search: Efficient Neural Architecture Search via Channel Pruning and Structural Reparameterization
As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2206.01198.
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 2026-08-12T06:34:41.77262+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T20:27:18.054852Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T15:57:36.232874Z
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 b344b1a0-2f93-4d9c-a25c-9ba8614f0daf · inbound
7B Fully Open Source Moxin-LLM/VLM -- From Pretraining to GRPO-based Reinforcement Learning Enhancement cites this paper.
7B Fully Open Source Moxin-LLM/VLM -- From Pretraining to GRPO-based Reinforcement Learning Enhancement Pruning-as-Search: Efficient Neural Architecture Search via Channel Pruning and Structural Reparameterization
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T20:27:18.054852Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a35a2dba-88bf-4d4c-9108-6cd63f24ed81 · inbound
Designing Semi-Structured Pruning of Graph Convolutional Networks for Skeleton-based Recognition cites this paper.
Designing Semi-Structured Pruning of Graph Convolutional Networks for Skeleton-based Recognition Pruning-as-Search: Efficient Neural Architecture Search via Channel Pruning and Structural Reparameterization
Reference 92
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T14:37:06.628669Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d6a01068-2488-45f7-aa7a-158b9df60c25 · inbound
Numerical Pruning for Efficient Autoregressive Models cites this paper.
Numerical Pruning for Efficient Autoregressive Models Pruning-as-Search: Efficient Neural Architecture Search via Channel Pruning and Structural Reparameterization
Reference 95
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T14:11:27.147459Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2be5c6be-c4e3-4c46-acc9-99166cfde2dd · inbound
Learning Coarse-to-Fine Pruning of Graph Convolutional Networks for Skeleton-based Recognition cites this paper.
Learning Coarse-to-Fine Pruning of Graph Convolutional Networks for Skeleton-based Recognition Pruning-as-Search: Efficient Neural Architecture Search via Channel Pruning and Structural Reparameterization
Reference 92
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T13:42:51.285314Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8f5d8d68-1c1f-4165-88b6-edc64b7301ef · inbound
Pruning Increases Orderedness in Recurrent Computation cites this paper.
Pruning Increases Orderedness in Recurrent Computation Pruning-as-Search: Efficient Neural Architecture Search via Channel Pruning and Structural Reparameterization
Reference 7
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T15:57:36.289878Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.