Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
KVPruner: Structural Pruning for Faster and Memory-Efficient Large Language Models
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2409.11057.
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 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-08T14:48:53.804404Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-13T20:28:14.163808Z
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 8a3a09ec-7afe-49f6-b34f-d893f9a8f504 · inbound
EfficientLLM: Scalable Pruning-Aware Pretraining for Architecture-Agnostic Edge Language Models cites this paper.
EfficientLLM: Scalable Pruning-Aware Pretraining for Architecture-Agnostic Edge Language Models KVPruner: Structural Pruning for Faster and Memory-Efficient Large Language Models
Reference 23
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T14:48:53.804404Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 11610039-0eb8-429d-a93a-37a43e2890be · inbound
ECG Foundation Models and Medical LLMs for Agentic Cardiovascular Intelligence at the Edge: A Review and Outlook cites this paper.
ECG Foundation Models and Medical LLMs for Agentic Cardiovascular Intelligence at the Edge: A Review and Outlook KVPruner: Structural Pruning for Faster and Memory-Efficient Large Language Models
Reference 108
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T20:28:14.165172Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.