Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Group Fisher Pruning for Practical Network Compression
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2108.00708.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T13:22:46.284667Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
25
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation e404fb81-d970-468a-afcb-4cac69586276 · inbound
Investigating Structural Pruning and Recovery Techniques for Compressing Multimodal Large Language Models: An Empirical Study cites this paper.
Investigating Structural Pruning and Recovery Techniques for Compressing Multimodal Large Language Models: An Empirical Study Group Fisher Pruning for Practical Network Compression
Reference 37
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T13:22:46.284667Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 02e6edda-dbbe-4cde-b92f-c64e37675c87 · inbound
Vanishing Contributions: A Unified Framework for Smooth and Iterative Model Compression cites this paper.
Vanishing Contributions: A Unified Framework for Smooth and Iterative Model Compression Group Fisher Pruning for Practical Network Compression
Reference 26
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T08:41:08.020901Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation c6e0f972-e783-4f52-b350-b1b57ed924d8 · inbound
Structural Pruning of Large Vision Language Models: A Comprehensive Study on Pruning Dynamics, Recovery, and Data Efficiency cites this paper.
Structural Pruning of Large Vision Language Models: A Comprehensive Study on Pruning Dynamics, Recovery, and Data Efficiency Group Fisher Pruning for Practical Network Compression
Reference 25
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-11T21:56:12.959101Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.